Alternatives to Syntho
Compare Syntho alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Syntho in 2026. Compare features, ratings, user reviews, pricing, and more from Syntho competitors and alternatives in order to make an informed decision for your business.
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Windocks
Windocks
Windocks is a leader in cloud native database DevOps, recognized by Gartner as a Cool Vendor, and as an innovator by Bloor research in Test Data Management. Novartis, DriveTime, American Family Insurance, and other enterprises rely on Windocks for on-demand database environments for development, testing, and DevOps. Windocks software is easily downloaded for evaluation on standard Linux and Windows servers, for use on-premises or cloud, and for data delivery of SQL Server, Oracle, PostgreSQL, and MySQL to Docker containers or conventional database instances. Windocks database orchestration allows for code-free end to end automated delivery. This includes masking, synthetic data, Git operations and access controls, as well as secrets management. Windocks can be installed on standard Linux or Windows servers in minutes. It can also run on any public cloud infrastructure or on-premise infrastructure. One VM can host up 50 concurrent database environments. -
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Titaniam
Titaniam
Titaniam provides enterprises and SaaS vendors with a full suite of data security/privacy controls in a single, enterprise grade solution. This includes highly advanced options such as encryption-in-use that enables encrypted search and analytics without decryption, and also traditional controls such as tokenization, masking, various types of encryption, and anonymization. Titaniam also offers BYOK/HYOK (bring/hold your own key) for data owners to control the security of their data. If attacked, Titaniam minimizes regulatory overhead by providing evidence that sensitive data retained encryption. Titaniam’s interoperable modules can be combined to support hundreds of architectures across multiple clouds, on-prem, and hybrid environments. Titaniam provides the equivalent of 3+ categories of solutions making it the most effective, and economical solution in the market. Titaniam is featured by Gartner, IDC, and TAG Cyber and has won coveted industry awards e.g. SINET16 and at RSAC2022. -
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DATPROF
DATPROF
Test Data Management solutions like data masking, synthetic data generation, data subsetting, data discovery, database virtualization, data automation are our core business. We see and understand the struggles of software development teams with test data. Personally Identifiable Information? Too large environments? Long waiting times for a test data refresh? We envision to solve these issues: - Obfuscating, generating or masking databases and flat files; - Extracting or filtering specific data content with data subsetting; - Discovering, profiling and analysing solutions for understanding your test data, - Automating, integrating and orchestrating test data provisioning into your CI/CD pipelines and - Cloning, snapshotting and timetraveling throug your test data with database virtualization. We improve and innovate our test data software with the latest technologies every single day to support medium to large size organizations in their Test Data Management. -
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Immuta
Immuta
Immuta is the market leader in secure Data Access, providing data teams one universal platform to control access to analytical data sets in the cloud. Only Immuta can automate access to data by discovering, securing, and monitoring data. Data-driven organizations around the world trust Immuta to speed time to data, safely share more data with more users, and mitigate the risk of data leaks and breaches. Founded in 2015, Immuta is headquartered in Boston, MA. Immuta is the fastest way for algorithm-driven enterprises to accelerate the development and control of machine learning and advanced analytics. The company's hyperscale data management platform provides data scientists with rapid, personalized data access to dramatically improve the creation, deployment and auditability of machine learning and AI. -
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Tonic
Tonic
Tonic automatically creates mock data that preserves key characteristics of secure datasets so that developers, data scientists, and salespeople can work conveniently without breaching privacy. Tonic mimics your production data to create de-identified, realistic, and safe data for your test environments. With Tonic, your data is modeled from your production data to help you tell an identical story in your testing environments. Safe, useful data created to mimic your real-world data, at scale. Generate data that looks, acts, and feels just like your production data and safely share it across teams, businesses, and international borders. PII/PHI identification, obfuscation, and transformation. Proactively protect your sensitive data with automatic scanning, alerts, de-identification, and mathematical guarantees of data privacy. Advanced sub setting across diverse database types. Collaboration, compliance, and data workflows — perfectly automated. -
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K2View
K2View
At K2View, we believe that every enterprise should be able to leverage its data to become as disruptive and agile as the best companies in its industry. We make this possible through our patented Data Product Platform, which creates and manages a complete and compliant dataset for every business entity – on demand, and in real time. The dataset is always in sync with its underlying sources, adapts to changes in the source structures, and is instantly accessible to any authorized data consumer. Data Product Platform fuels many operational use cases, including customer 360, data masking and tokenization, test data management, data migration, legacy application modernization, data pipelining and more – to deliver business outcomes in less than half the time, and at half the cost, of any other alternative. The platform inherently supports modern data architectures – data mesh, data fabric, and data hub – and deploys in cloud, on-premise, or hybrid environments. -
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Gretel
Gretel.ai
Privacy engineering tools delivered to you as APIs. Synthesize and transform data in minutes. Build trust with your users and community. Gretel’s APIs grant immediate access to creating anonymized or synthetic datasets so you can work safely with data while preserving privacy. Keeping the pace with development velocity requires faster access to data. Gretel is accelerating access to data with data privacy tools that bypass blockers and fuel Machine Learning and AI applications. Keep your data contained by running Gretel containers in your own environment or scale out workloads to the cloud in seconds with Gretel Cloud runners. Using our cloud GPUs makes it radically more effortless for developers to train and generate synthetic data. Scale workloads automatically with no infrastructure to set up and manage. Invite team members to collaborate on cloud projects and share data across teams. -
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Protecto
Protecto
While enterprise data is exploding and scattered across various systems, oversight of driving privacy, data security, and governance has become very challenging. As a result, businesses hold significant risks in the form of data breaches, privacy lawsuits, and penalties. Finding data privacy risks in an enterprise is a complex, and time-consuming effort that takes months involving a team of data engineers. Data breaches and privacy laws are requiring companies to have a better grip on which users have access to the data, and how the data is used. But enterprise data is complex, so even if a team of engineers works for months, they will have a tough time isolating data privacy risks or quickly finding ways to reduce them.Starting Price: Usage based -
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MOSTLY AI
MOSTLY AI
As physical customer interactions shift into digital, we can no longer rely on real-life conversations. Customers express their intents, share their needs through data. Understanding customers and testing our assumptions about them also happens through data. And privacy regulations such as GDPR and CCPA make a deep understanding even harder. The MOSTLY AI synthetic data platform bridges this ever-growing gap in customer understanding. A reliable, high-quality synthetic data generator can serve businesses in various use cases. Providing privacy-safe data alternatives is just the beginning of the story. In terms of versatility, MOSTLY AI's synthetic data platform goes further than any other synthetic data generator. MOSTLY AI's versatility and use case flexibility make it a must-have AI tool and a game-changing solution for software development and testing. From AI training to explainability, bias mitigation and governance to realistic test data with subsetting, referential integrity. -
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CloudTDMS
Cloud Innovation Partners
CloudTDMS solution is a No-Code platform having all necessary functionalities required for Realistic Data Generation. CloudTDMS, your one stop for Test Data Management. Discover & Profile your Data, Define & Generate Test Data for all your team members : Architects, Developers, Testers, DevOPs, BAs, Data engineers, and more ... CloudTDMS automates the process of creating test data for non-production purposes such as development, testing, training, upgrading or profiling. While at the same time ensuring compliance to regulatory and organisational policies & standards. CloudTDMS involves manufacturing and provisioning data for multiple testing environments by Synthetic Test Data Generation as well as Data Discovery & Profiling. Benefit from CloudTDMS No-Code platform to define your data models and generate your synthetic data quickly in order to get faster return on your “Test Data Management” investments. CloudTDMS solves the following challenges : -Regulatory ComplianceStarting Price: Starter Plan : Always free -
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GenRocket
GenRocket
Enterprise synthetic test data solutions. In order to generate test data that accurately reflects the structure of your application or database, it must be easy to model and maintain each test data project as changes to the data model occur throughout the lifecycle of the application. Maintain referential integrity of parent/child/sibling relationships across the data domains within an application database or across multiple databases used by multiple applications. Ensure the consistency and integrity of synthetic data attributes across applications, data sources and targets. For example, a customer name must always match the same customer ID across multiple transactions simulated by real-time synthetic data generation. Customers want to quickly and accurately create their data model as a test data project. GenRocket offers 10 methods for data model setup. XTS, DDL, Scratchpad, Presets, XSD, CSV, YAML, JSON, Spark Schema, Salesforce. -
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Sixpack
PumpITup
Sixpack is a data management platform designed to streamline synthetic data for testing purposes. Unlike traditional test data generation, Sixpack provides an endless supply of synthetic data, helping testers and automated tests avoid conflicts and resource bottlenecks. It focuses on flexibility by enabling allocation, pooling, and instant data generation while keeping data quality high and privacy intact. Key features include easy setup, seamless API integration, and the ability to support complex test environments. Sixpack integrates directly with QA processes, so teams save time on managing data dependencies, minimize data overlap, and prevent test interference. Its dashboard offers a clear view of active data sets, and testers can allocate or pool data according to project needs.Starting Price: $0 -
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Private AI
Private AI
Safely share your production data with ML, data science, and analytics teams while safeguarding customer trust. Stop fiddling with regexes and open-source models. Private AI efficiently anonymizes 50+ entities of PII, PCI, and PHI across GDPR, CPRA, and HIPAA in 49 languages with unrivaled accuracy. Replace PII, PCI, and PHI in text with synthetic data to create model training datasets that look exactly like your production data without compromising customer privacy. Remove PII from 10+ file formats, such as PDF, DOCX, PNG, and audio to protect your customer data and comply with privacy regulations. Private AI uses the latest in transformer architectures to achieve remarkable accuracy out of the box, no third-party processing is required. Our technology has outperformed every other redaction service on the market. Feel free to ask us for a copy of our evaluation toolkit to test on your own data. -
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SecuPi
SecuPi
SecuPi provides an overarching data-centric security platform, delivering fine-grained access control (ABAC), Database Activity Monitoring (DAM) and de-identification using FPE encryption, physical and dynamic masking and deletion (RTBF). SecuPi offers wide coverage across packaged and home-grown applications, direct access tools, big data, and cloud environments. One data security platform for monitoring, controlling, encrypting, and classifying data across all cloud & on-prem platforms seamlessly with no code changes. Agile and efficient configurable platform to meet current & future regulatory and audit requirements. No source-code changes with fast & cost-efficient implementation. SecuPi’s fine-grain data access controls protect sensitive data so users get access only to data they are entitled to view, and no more. Seamlessly integrate with Starburst/Trino for automated enforcement of data access policies and data protection operations. -
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Datanamic Data Generator
Datanamic
Datanamic Data Generator is a powerful data generator that allows developers to easily populate databases with thousands of rows of meaningful and syntactically correct test data for database testing purposes. An empty database is not useful for making sure your application will work as designed. You need test data. Writing your own test data generators or scripts is time consuming. Datanamic Data Generator will help you. The tool can be used by DBAs, developers, or testers, who need sample data to test a database-driven application. Datanamic Data Generator makes database test data generation easy and painless. It reads your database and displays tables and columns with their data generation settings. Only a few simple entries are necessary to generate comprehensive (realistic) test data. The tool can be used to generate test data from scratch or from existing data.Starting Price: €59 per month -
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Piiano
Piiano
Emerging privacy policies often conflict with the architectures of enterprise systems that were not designed with sensitive data protection in mind. Piiano pioneers data privacy engineering for the cloud, offering the industry’s first personal data protection and management platform to transform how enterprises build privacy-forward architecture and operationalize privacy practices. Piiano provides a pre-built, developer-friendly infrastructure to dramatically ease the adoption or acceleration of enterprise privacy engineering and help developers build privacy-by-design architecture. This engineering infrastructure safeguards sensitive customers’ data, preempts breaches, and helps enterprises comply with privacy regulations as they evolve. The Vault is a dedicated, protected database for centralizing sensitive information that developers can install into enterprise VPC (Virtual Private Cloud). This ensures that the vault–and everything in it–is only accessible to the enterprise. -
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HushHush Data Masking
HushHush
Today’s businesses face significant punishment if they do not meet the ever-increasing privacy requirements of both regulators and the public. Vendors need to keep abreast by adding new algorithms to protect sensitive data such as PII and PHI. HushHush stays at the forefront of privacy protection (Patents: US9886593, US20150324607A1, US10339341) with its PII data discovery and anonymization tool workbench (also known as data de-identification, data masking, and obfuscation software). It helps you find your and your customer's sensitive data, classify it, anonymize it, and comply with GDPR, CCPA, HIPAA / HITECH, and GLBA requirements. Use a collection of rule-based atomic add-on anonymization components to configure comprehensive and secure data anonymization solutions. HushHush components are out-of-the box solutions designed to anonymize both direct identifiers (SSN, credit cards, names, addresses, phone numbers, etc.) as well as indirect identifiers, with both fixed algorithms. -
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Informatica Persistent Data Masking
Informatica
Retain context, form, and integrity while preserving privacy. Enhance data protection by de-sensitizing and de-identifying sensitive data, and pseudonymize data for privacy compliance and analytics. Obscured data retains context and referential integrity remain consistent, so the masked data can be used in testing, analytics, or support environments. As a highly scalable, high-performance data masking solution, Informatica Persistent Data Masking shields confidential data—such as credit card numbers, addresses, and phone numbers—from unintended exposure by creating realistic, de-identified data that can be shared safely internally or externally. It also allows you to reduce the risk of data breaches in nonproduction environments, produce higher-quality test data and streamline development projects, and ensure compliance with data-privacy mandates and regulations. -
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Privitar
Privitar
The Privitar Data Provisioning Platform is a comprehensive, modern data provisioning platform that enables collaboration across data owners, data consumers and data guardians to deliver safe data – within and beyond an organization – in a fraction of the time compared with traditional approaches. Privitar is making sensitive data highly accessible through the application of privacy enhancing technologies, so organizations like yours can optimize business and customer outcomes. Countdown to launch with us and learn why only Privitar has the right combination of technology and expertise to create a safe and modern data provisioning ecosystem. Early access gets you a front row seat as we embark on the path of empowering organizations to use all of their data safely! For your business, we enable rapid, self-service access to safe data to drive new revenue opportunities, all while seamlessly integrating within your existing infrastructure to reduce cost and speed time to value. -
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PHEMI Health DataLab
PHEMI Systems
The PHEMI Trustworthy Health DataLab is a unique, cloud-based, integrated big data management system that allows healthcare organizations to enhance innovation and generate value from healthcare data by simplifying the ingestion and de-identification of data with NSA/military-grade governance, privacy, and security built-in. Conventional products simply lock down data, PHEMI goes further, solving privacy and security challenges and addressing the urgent need to secure, govern, curate, and control access to privacy-sensitive personal healthcare information (PHI). This improves data sharing and collaboration inside and outside of an enterprise—without compromising the privacy of sensitive information or increasing administrative burden. PHEMI Trustworthy Health DataLab can scale to any size of organization, is easy to deploy and manage, connects to hundreds of data sources, and integrates with popular data science and business analysis tools. -
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IBM InfoSphere® Optim™ Data Privacy provides extensive capabilities to effectively mask sensitive data across non-production environments, such as development, testing, QA or training. To protect confidential data this single offering provides a variety of transformation techniques that substitute sensitive information with realistic, fully functional masked data. Examples of masking techniques include substrings, arithmetic expressions, random or sequential number generation, date aging, and concatenation. The contextually accurate masking capabilities help masked data retain a similar format to the original information. Apply a range of masking techniques on-demand to transform personally-identifying information and confidential corporate data in applications, databases and reports. Data masking features help you to prevent misuse of information by masking, obfuscating, and privatizing personal information that is disseminated across non-production environments.
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Mimic
Facteus
Advanced technology and services to safely transform and enhance sensitive data into actionable insights, help drive innovation, and open new revenue streams. Using the Mimic synthetic data engine, companies can safely synthesize their data assets, protecting consumer privacy information from being exposed, while still maintaining the statistical relevancy of the data. The synthetic data can then be used for internal initiatives like analytics, machine learning and AI, marketing and segmentation activities, and new revenue streams through external data monetization. Mimic enables you to safely move statistically-relevant synthetic data to the cloud ecosystem of your choice to get the most out of your data. Analytics, insights, product development, testing, and third-party data sharing can all be done in the cloud with the enhanced synthetic data, which has been certified to be compliant with regulatory and privacy laws. -
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Statice
Statice
We offer data anonymization software that generates entirely anonymous synthetic datasets for our customers. The synthetic data generated by Statice contains statistical properties similar to real data but irreversibly breaks any relationships with actual individuals, making it a valuable and safe to use asset. It can be used for behavior, predictive, or transactional analysis, allowing companies to leverage data safely while complying with data regulations. Statice’s solution is built for enterprise environments with flexibility and security in mind. It integrates features to guarantee the utility and privacy of the data while maintaining usability and scalability. It supports common data types: Generate synthetic data from structured data such as transactions, customer data, churn data, digital user data, geodata, market data, etc We help your technical and compliance teams validate the robustness of our anonymization method and the privacy of your synthetic dataStarting Price: Licence starting at 3,990€ / m -
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TCS MasterCraft DataPlus
Tata Consultancy Services
The users of data management software are primarily from enterprise business teams. This requires the data management software to be highly user-friendly, automated and intelligent. Additionally, data management activities must adhere to various industry-specific and data protection related regulatory requirements. Further, data must be adequate, accurate, consistent, of high quality and securely accessible so that business teams can make informed and data-driven strategic business decisons. Enables an integrated approach for data privacy, data quality management, test data management, data analytics and data modeling. Efficiently addresses growing volumes of data efficiently, through service engine-based architecture. Handles niche data processing requirements, beyond out of box functionality, through a user-defined function framework and python adapter. Provides a lean layer of governance surrounding data privacy and data quality management. -
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Databunker
Databunker
Databunker is a lightning-fast, open-source vault developed in Go for secure storage of sensitive personal records. Protect user records from SQL and GraphQL injections with a simple API. Streamline GDPR, HIPAA, ISO 27001, and SOC2 compliance. Databunker is a special secure storage system designed to protect: - Personally Identifiable Information (PII) - Protected Health Information (PHI) - Payment Card Industry (PCI) data - Know Your Customer (KYC) recordsStarting Price: Free -
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DataSunrise Database Security
DataSunrise
Data-Centric high-performance database security software. Regulatory Compliance with SOX, HIPAA, GDPR, PCI DSS and other privacy laws and standards. Hybrid and Multi-Cloud Database Security Proxy on AWS, Azure, Google and On-Prem. Sensitive and PII data auditing, discovery and active protection. Data Auditing enables real-time tracking of user actions and changes made to data and databases to ensure compliance-ready environment, increased visibility. Database Firewall, role based & location aware Data Access Control & Protection. Secure corporate databases in cloud & on-prem against hostile, negligent actions. Secures sensitive data in development and testing environments; Encryption; completely eliminates the possibility to reverse engineer the masked data. Real-time role and location based data masking of production data. Prevents exposure of sensitive privacy data while production data is not changed physically. -
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Protegrity
Protegrity
Our platform allows businesses to use data—including its application in advanced analytics, machine learning, and AI—to do great things without worrying about putting customers, employees, or intellectual property at risk. The Protegrity Data Protection Platform doesn't just secure data—it simultaneously classifies and discovers data while protecting it. You can't protect what you don't know you have. Our platform first classifies data, allowing users to categorize the type of data that can mostly be in the public domain. With those classifications established, the platform then leverages machine learning algorithms to discover that type of data. Classification and discovery finds the data that needs to be protected. Whether encrypting, tokenizing, or applying privacy methods, the platform secures the data behind the many operational systems that drive the day-to-day functions of business, as well as the analytical systems behind decision-making. -
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Informatica Test Data Management
Informatica
We help you discover, create, and subset test data; visualize test data coverage; and protect data so you can focus on development. Automate provisioning of masked, subsetted, and synthetically generated data to meet development and testing needs. Identify sensitive data locations quickly with consistent masking in and across databases. Store, augment, share, and reuse test datasets to improve testers’ efficiency. Provision smaller data sets to minimize infrastructure requirements and speed performance. Use our comprehensive set of masking techniques to consistently protect data across applications. Support packaged applications to ensure solution integrity and speed deployments. Engage risk, compliance, and audit teams to align with data governance initiatives. Improve test efficiency with reliable, trusted production data sets; reduce server and storage footprints with data set sizes targeted for each team. -
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Borneo
Borneo
Borneo is a real-time data security and privacy observability platform designed to help organizations discover, remediate, and govern data risks while ensuring privacy and compliance. It enables users to discover where health data, financial data, and PII are stored across unstructured data, SaaS apps, and public cloud environments. Borneo's risk correlation engine identifies data that violates security frameworks and privacy regulations, prompting immediate action. It offers automatic remediation through data masking, access changes, and encryption, and continuously monitors changes across the data landscape to maintain compliance and eliminate regulatory risk. Built by security practitioners from Uber, Facebook, and Yahoo, Borneo is crafted to handle data at scale. It features a powerful connector framework to integrate across diverse data landscapes, supports flexible and modular deployment, and ensures that data never leaves the user's cloud environment. -
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Benerator
Benerator
Describe your data model on an abstract level in XML. Involve your business people as no developer skills are necessary. Use a wide range of function libraries to fake realistic data. Write your own extensions in Javascript or Java. Integrate your data processes into Gitlab CI or Jenkins. Generate, anonymize, and migrate with Benerator’s model-driven data toolkit. Define processes to anonymize or pseudonymize data in plain XML on an abstract level without the need for developer skills. Stay GDPR compliant with your data and protect the privacy of your customers. Mask and obfuscate sensitive data for BI, test, development, or training purposes. Combine data from various sources (subsetting) and keep the data integrity. Migrate and transform your data in multisystem landscapes. Reuse your testing data models to migrate production environments. Keep your data consistent and reliable in a microsystem architecture. -
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Sudo Platform
Anonyome Labs
Sudo Platform is an API-first, developer-focused ecosystem that delivers the tools necessary to empower our partners to quickly and completely deliver to end-user consumers the necessary capabilities to protect and control their personal information while navigating the digital world. It provides a modular, quick to implement, and powerful collection of the most important digital privacy and cyber safety tools. including safe and private browsing, password management, VPN, virtual cards, encrypted and open communications, and decentralized identity. This developer-focused platform includes: Developer-focused documentation API-first ecosystem SDK source code via GitHub Sample applications for test-to-deploy of various capabilities Vendor-brandable (white-label) apps for quick go-to-market deployments. -
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Oracle Data Safe
Oracle
Data Safe is a unified control center for your Oracle Databases which helps you understand the sensitivity of your data, evaluate risks to data, mask sensitive data, implement and monitor security controls, assess user security, monitor user activity, and address data security compliance requirements. Whether you’re using Oracle Autonomous Database. Oracle Database Cloud Service (exadata, virtual machine, or bare metal), or Oracle Databases on-premises in your own data center, Data Safe delivers essential data security capabilities that help you reduce risk and improve security. Assess user risk by highlighting critical users, roles and privileges. Configure audit policies and collect user activity to identify unusual behavior. Discover sensitive data and understand where it is located. Remove risk from non-production data sets by masking sensitive data. -
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Cloud Compliance
Cloud Compliance
Operationalize privacy compliance and data security on Salesforce with the most comprehensive suite of products. The success of privacy programs requires thorough data inventory and risk assessment. However, most organizations end up overlooking pockets of data and struggle with manual processes and spreadsheets. Our Personal Data Inventory product is designed to automate and streamline DPIA and enterprise data inventory flows. Make it easy for your organization to have an accurate data inventory and clear risk assessment. Most organizations are seeing an increase in privacy right requests. Trying to meet these requests manually is inconsistent, error-prone, and increases the risk of non-compliance. Our Privacy Rights Automation product enables self-service and automates all privacy rights related activities. Mitigate the risk of non-compliance with a standardized and error-free solution. -
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Informatica Dynamic Data Masking
Informatica
Your IT organization can apply sophisticated masking to limit sensitive data access with flexible data masking rules based on a user’s authentication level. Blocking, auditing, and alerting your users, IT personnel, and outsourced teams who access sensitive information, it ensures compliance with your security policies and industry and civil privacy regulations. Easily customize data-masking solutions for different regulatory or business requirements. Protect personal and sensitive information while supporting offshoring, outsourcing, and cloud-based initiatives. Secure big data by dynamically masking sensitive data in Hadoop. -
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BizDataX
Ekobit
BizDataX is a data masking that provides test data of production-level quality. It enables compliance with GDPR and other regulations by masking customers' identity while preparing data for testers and developers. By using masked/anonymized data instead of production data, the risk is significantly reduced. Focus on policy management, business requirements, sensitive data governance and other regulations. Track inventory of databases, data sources, tables and want to know where sensitive data is located. Manage large customer databases and exchange data with online partner shops and parcel delivery companies. Management of medical records is heavily regulated and regulatory compliance can be achieved with data anonymization. -
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PieEye
PieEye
PieEye simplifies the complex process of managing user consent and compliance with privacy regulations, such as GDPR and CPRA/CCPA. The quickest, easiest, most efficient, and most automated solution for any ecommerce business; large, medium, or small. There is no need to do headstands and spend weeks or even months on tedious compliance work when our platform can get you up and running in minutes. Easy-to-install, easy-to-install, and automate, PieEye allows you to streamline your compliance efforts and focus on what really matters: growing your business. Discover how effortless compliance can be. With more data privacy laws, cookie compliance is more important than ever. Our cutting-edge cookie banner makes your website fully compliant with all regulations, safeguarding your customers’ data rights and protecting you. Our automated platform streamlines the entire process, enabling you to easily manage requests and ensure compliance with all relevant regulations.Starting Price: $29 per month -
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EMS Data Generator for MySQL
EMS Software Development
EMS Data Generator for MySQL is an impressive tool for generating test data to MySQL database tables with the possibility to save and edit scripts. The utility can help you to simulate the database production environment and allows you to populate several MySQL database tables with test data simultaneously, define tables and fields for generating data, set value ranges, generate MySQL char fields by mask, define lists of values manually or select them from SQL queries, set generation parameters for each field type and has many other features to generate MySQL test data in a simple and direct way. Data Generator for MySQL also provides a console application, which allows you to generate MySQL test data in one-touch by using generation templates.Starting Price: $60 per year -
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Ohalo
Ohalo
Ohalo's Data X-Ray platform automates data governance tasks like: - Data Discovery & Classification - Data Mapping & Cataloguing - Redacting Files containing sensitive personal information - File Analysis & Data Extraction ⚡️ML-Driven Data Governance | 100,000 words/second | 300+ built-in Integrations | Integration with any DLP/SIEM | 360-degree Unstructured Data Visibility | Agentless | Supports 100s of formats | Find PII, payment card information (PCI), and protected health information (ePHI). | Custom connectors for individual data sources (bespoke/legacy) ⚡️ Designed for enterprises, Data X-Ray is provided as a self-managed or fully-managed service. Our customers rely on Data X-Ray for file activity monitoring, security enhancement, and privacy compliance. ⚡️ Deploy Data X-Ray in hours in cloud and on-premise environments ⚡️ Find sensitive data in minutes ⚡️ Easily classify files and records from multiple file repositories and locations -
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Synth
Synth
Synth is an open-source data-as-code tool that provides a simple CLI workflow for generating consistent data in a scalable way. Use Synth to generate correct, anonymized data that looks and quacks like production. Generate test data fixtures for your development, testing, and continuous integration. Generate data that tells the story you want to tell. Specify constraints, relations, and all your semantics. Seed development and environments and CI. Anonymize sensitive production data. Create realistic data to your specifications. Synth uses a declarative configuration language that allows you to specify your entire data model as code. Synth can import data straight from existing sources and automatically create accurate and versatile data models. Synth supports semi-structured data and is database agnostic, playing nicely with SQL and NoSQL databases. Synth supports generation for thousands of semantic types such as credit card numbers, email addresses, and more.Starting Price: Free -
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Data is an invaluable business asset. With the right AI model, it’s possible to use data to build and understand customer profiles, look for trends, and identify new business opportunities. But it requires huge volumes of data to develop accurate and robust AI models, and that’s a challenge, from both a data quality and quantity perspective. In addition, stringent regulations, most notably GDPR, restrict the use of certain sensitive data, like customer data. It’s time for a new approach. Especially in a software testing environment where good quality testing data is hard to access. We typically see actual customer data being used, which risks GDPR non-compliance and ensuing heavy financial fines. Artificial Intelligence (AI) is expected to increase business productivity by at least 40% but businesses struggle to deploy or fully unlock AI solutions due to data-related challenges. ADA generates synthetic data using advanced deep learning.
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Syntheticus
Syntheticus
Syntheticus® empowers data exchange and overcomes limitations in data access, scarcity, and bias - at scale. With our synthetic data platform, you generate high-quality and compliant data samples tailored to your business needs and analytics goals. With synthetic data, you easily tap into a wide range of high-quality sources that are not always available in the real world. By accessing high-quality, consistent data, you conduct more reliable research, leading to better products, services, and business decisions. With fast, reliable data sources at your fingertips, you accelerate product development cycles and improve time-to-market. Synthetic data is designed to be private and secure by default, protecting sensitive data and maintaining compliance with privacy laws and regulations. -
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Synthesized
Synthesized
Power up your AI and data projects with the most valuable data At Synthesized, we unlock data's full potential by automating all stages of data provisioning and data preparation with a cutting-edge AI. We protect from privacy and compliance hurdles by virtue of the data being synthesized through the platform. Software for preparing and provisioning of accurate synthetic data to build better models at scale. Businesses solve the problem of data sharing with Synthesized. 40% of companies investing in AI cannot report business gains. Stay ahead of your competitors and help data scientists, product and marketing teams focus on uncovering critical insight with our simple-to-use platform for data preparation, sanitization and quality assessment. Testing data-driven applications is difficult without representative datasets and this leads to issues when services go live. -
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DOT Anonymizer
DOT Anonymizer
Mask your personal data while ensuring it looks and acts like real data. Software development needs realistic test data. DOT Anonymizer masks your test data while ensuring its consistency, across all your data sources and DBMS. The use of personal or identifying data outside of production (development, testing, training, BI, external service providers, etc.) carries a major risk of data leak. Increasing regulations across the world require companies to anonymize/pseudonymize personal or identifying data. Anonymization enables you to retain the original data format. Your teams work with fictional but realistic data. Manage all your data sources and maintain their usability. Invoke DOT Anonymizer functions from your own applications. Consistency of anonymizations across all DBMS and platforms. Preserve relations between tables to guarantee realistic data. Anonymize all database types and files like CSV, XML, JSON, etc.Starting Price: €488 per month -
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YData
YData
Adopting data-centric AI has never been easier with automated data quality profiling and synthetic data generation. We help data scientists to unlock data's full potential. YData Fabric empowers users to easily understand and manage data assets, synthetic data for fast data access, and pipelines for iterative and scalable flows. Better data, and more reliable models delivered at scale. Automate data profiling for simple and fast exploratory data analysis. Upload and connect to your datasets through an easily configurable interface. Generate synthetic data that mimics the statistical properties and behavior of the real data. Protect your sensitive data, augment your datasets, and improve the efficiency of your models by replacing real data or enriching it with synthetic data. Refine and improve processes with pipelines, consume the data, clean it, transform your data, and work its quality to boost machine learning models' performance. -
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DataCebo Synthetic Data Vault (SDV)
DataCebo
The Synthetic Data Vault (SDV) is a Python library designed to be your one-stop shop for creating tabular synthetic data. The SDV uses a variety of machine learning algorithms to learn patterns from your real data and emulate them in synthetic data. The SDV offers multiple models, ranging from classical statistical methods (GaussianCopula) to deep learning methods (CTGAN). Generate data for single tables, multiple connected tables, or sequential tables. Compare the synthetic data to the real data against a variety of measures. Diagnose problems and generate a quality report to get more insights. Control data processing to improve the quality of synthetic data, choose from different types of anonymization, and define business rules in the form of logical constraints. Use synthetic data in place of real data for added protection, or use it in addition to your real data as an enhancement. The SDV is an overall ecosystem for synthetic data models, benchmarks, and metrics.Starting Price: Free -
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NMTY Enterprise
NMTY
NMTY Enterprise helps you protect all your privacy-sensitive data within your organization, regardless if it is stored in databases or files. Make NMTY Enterprise part of your IT environment and immediately anonymize all data sources that need to be protected. NMTY Enterprise makes it possible to anonymize data regardless of how it is stored, from databases to individual files. Anonymize data stored in a database or in separate files such as CSV and XML. Data is always anonymized directly within the source. This prevents non-anonymized data from being duplicated unnecessarily. Connections to your data sources support integrated authentication and are always encrypted when stored. In addition to anonymizing datasets, it is also possible to directly anonymize data processed within documents and images. Our solutions are developed based on the latest innovations and integrate directly into your existing processes. This way we ensure we always achieve the maximum result. -
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AuricVault® Tokenization
Auric Systems International
The AuricVault® tokenization service secures your vitally sensitive financial and personal data by safely storing that data and replacing the data in your system with a token. Tokens are random strings of numbers and letters that have no relationship to the stored data. If someone stole all your tokens, they still would not have any of your sensitive data. Tokenization provides what is called data separation. Data separation ensures that no single entity has all the data at one time. Auric's tokenization solution provides fine-grained permissions for one or more parties to access sensitive tokenized data. Depending on your business model, using the AuricVault® tokenization service may exclude your systems and servers from PCI scope. We help businesses protect billions of dollars and millions of transactions securely, safely, and simply.Starting Price: $300 per year -
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LeapYear
LeapYear Technologies
Differential privacy is a mathematically proven standard of data privacy that ensures all data can be used for analytics and machine learning without the risk of compromising information about individual records. LeapYear’s differentially private system protects some of the world’s most sensitive datasets, including social media data, medical information, and financial transactions. The system ensures analysts, data scientists, and researchers can derive value from all of the data, including data of highly sensitive fields, while protecting all facts about individuals, entities, and transactions. Traditional approaches, such as aggregation, anonymization, or masking degrade data value and can be easily exploited to reconstruct sensitive information. LeapYear’s implementation of differential privacy provides mathematically proven assurances that information about individual records cannot be reconstructed, while also enabling all of the data to be leveraged for reporting -
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Anonomatic
Anonomatic
Safely store, anonymize, mask, mine, redact, and share sensitive data with 100% data accuracy and full international data privacy compliance. Reap significant time and cost savings, with no loss of functionality, when you separate PII from identified data. Embed PII Vault to create innovative solutions, reduce time to market, and deliver the most PII secure solutions anywhere. Unlock data to deliver more accurate and targeted messaging. Provide one, simple step to anonymize all data before it reaches your platform. Combine disparate, anonymous data sets at the individual level without ever receiving PII once that data has been anonymized with Poly- Anonymization™. Replace PII with a compliant multi-value, non-identifying key used in anonymous data matching to link data from multiple organizations. -
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Qlik Gold Client
Qlik
Qlik Gold Client improves the efficiency, cost and security of managing test data in SAP environments. Qlik Gold Client is designed to eliminate development workarounds by easily moving configuration, master, and transactional data subsets into testing environments. Rapidly define, copy and synchronize transactional data from production to non-production targets. Identify, select, and delete non-production data. Manage extensive and powerful data transformations through a clean and easy-to-use interface. Automate data selection and enable hands-free test data refresh cycles, reducing time and effort for test data management. Qlik Gold Client provides several options to protect PII data in non-production environments via data masking. Data masking applies a set of rules to “scramble” your production data when it’s replicated to a non-production environment.
