Alternatives to Subsalt
Compare Subsalt alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Subsalt in 2026. Compare features, ratings, user reviews, pricing, and more from Subsalt competitors and alternatives in order to make an informed decision for your business.
-
1
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. -
2
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. -
3
IRI FieldShield
IRI, The CoSort Company
IRI FieldShield® is powerful and affordable data discovery and masking software for PII in structured and semi-structured sources, big and small. Use FieldShield utilities in Eclipse to profile, search and mask data at rest (static data masking), and the FieldShield SDK to mask (or unmask) data in motion (dynamic data masking). Classify PII centrally, find it globally, and mask it consistently. Preserve realism and referential integrity via encryption, pseudonymization, redaction, and other rules for production and test environments. Delete, deliver, or anonymize data subject to DPA, FERPA, GDPR, GLBA, HIPAA, PCI, POPI, SOX, etc. Verify compliance via human- and machine-readable search reports, job audit logs, and re-identification risk scores. Optionally mask data as you map it. Apply FieldShield functions in IRI Voracity ETL, federation, migration, replication, subsetting, or analytic jobs. Or, run FieldShield from Actifio, Commvault or Windocks to mask DB clones. -
4
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. -
5
Nymiz
Nymiz
Hours spent anonymizing data manually is time taken away from actual work. When data isn’t easily shareable, information gets trapped, creating silos within the organization and leading to poor knowledge management. The constant worry of whether shared data is compliant with ever-evolving regulations (GDPR, CCPA, HIPAA & more). Nymiz securely anonymizes personal data, through reversible or irreversible methods. The original data is replaced with asterisks, tokens or synthetic surrogates to improve privacy while maintaining the value of the information. By recognizing context-specific data like names, phone numbers, and social security numbers, we achieve superior results compared to tools that lack artificial intelligence capabilities. Additional security layer at the data level. Anonymized or pseudonymized information has no practical value if it is stolen through a security breach or exposed by human errors. -
6
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 -
7
Soflab G.A.L.L.
Soflab Technology Sp. z o.o.
The Soflab G.A.L.L. application is designed to anonymize sensitive data in non-production environments, enabling the generation of high-quality synthetic data that remains consistent with real data and supports reliable testing. At the same time, it ensures full protection of sensitive information, effectively preventing data leaks. Reduced data breach risk by replacing real data with artificial equivalents and detecting sensitive or erroneous records. Lower legal and financial exposure while protecting customer transactional data. Unified anonymization across non-production systems ensures a consistent data model and preserved production relationships. Synthetic data, generated from key production attributes, maintains statistical consistency for BI and AI. A central test data repository enables controlled reuse, lowers maintenance costs, accelerates deployments (up to 5 days), and supports simulation and reusable scenarios. -
8
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. -
9
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. -
10
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. -
11
DataGen
DataGen
DataGen is a leading AI platform specializing in synthetic data generation and custom generative AI models for machine learning projects. Their flagship product, SynthEngyne, supports multi-format data generation including text, images, tabular, and time-series data, ensuring privacy-compliant, high-quality training datasets. The platform offers scalable, real-time processing and advanced quality controls like deduplication to maintain dataset fidelity. DataGen also provides professional AI development services such as model deployment, fine-tuning, synthetic data consulting, and intelligent automation systems. With flexible pricing plans ranging from free tiers for individuals to custom enterprise solutions, DataGen caters to a wide range of users. Their solutions serve diverse industries including healthcare, finance, automotive, and retail. -
12
AnalyticDiD
Fasoo
De-identify sensitive data, including personally identifiable information (PII), through pseudonymization and anonymization for secondary use or analysis, such as comparative effectiveness studies, policy assessment, and life sciences research. This is critical as organizations gather and compile large amounts of business data to understand trends, gain insights into customer preferences, and develop new innovations. Regulations such as HIPAA and GDPR require that data be de-identified, but the challenge is that many de-identification tools focus on eliminating personal identifiers, but make it difficult to use the data. Transform PII into data that cannot be used to identify data while ensuring privacy using data anonymization and pseudonymization techniques. This allows you to effectively analyze large amounts of data without violating privacy regulations. De-identify data using selected methods and privacy models from broad areas of data de-identification and statistics. -
13
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. -
14
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. -
15
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. -
16
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. -
17
OpenText Data Privacy & Protection Foundation (Voltage) provides organizations with quantum-ready, format-preserving security that protects sensitive data without disrupting workflows or analytics. It helps companies meet evolving regulatory requirements by securing information at rest, in motion, and in use across hybrid and cloud environments. With NIST-standardized Format-Preserving Encryption and stateless key management, the platform delivers high-performance protection at enterprise scale. Its persistent data security approach ensures that sensitive information remains safeguarded throughout its lifecycle, even as it moves across systems and analytics platforms. Trusted globally across more than 50 countries, the solution is relied on by major financial, healthcare,& retail organizations to secure billions of daily data events. By combining proven cryptography with flexible integrations, OpenText enables organizations to reduce breach risk while maintaining operational agility.
-
18
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 -
19
syntheticAIdata
syntheticAIdata
syntheticAIdata is your partner in creating synthetic data that enables you to craft diverse datasets effortlessly and at scale. Utilizing our solution doesn’t just mean significant cost reductions; it means ensuring privacy, regulatory compliance, and expediting your AI products' journey to the market. Let syntheticAIdata be the catalyst that transforms your AI aspirations into achievements. Synthetic data is generated on a large scale and can cover many scenarios when real data is insufficient. A variety of annotations can be automatically generated. This greatly shortens the time for data collection and tagging. Minimize costs for data collection and tagging by generating synthetic data on a large scale. Our user-friendly and no-code solution empowers even those without technical expertise to easily generate synthetic data. With seamless one-click integration with leading cloud platforms, our solution is the most convenient to use on the market. -
20
Aindo
Aindo
Accelerate time-consuming data processing steps, including structuring, labeling, and preprocessing. Manage your data in one central, easy-to-integrate platform. Increase data accessibility rapidly through privacy-protecting synthetic data and user-friendly exchange platforms. The Aindo synthetic data platform allows you to securely exchange data across departments, with external service providers, partners, and the artificial intelligence community. Explore new synergies through synthetic data exchange and collaboration. Acquire missing data openly and securely. Provide comfort and trust to your clients and stakeholders. The Aindo synthetic data platform removes data inaccuracies and implicit bias for fair and complete insights. Augment information to make databases robust to special events. Balance datasets that misrepresent true populations for a fair and accurate overall depiction. Fill in data gaps in a sound and exact manner. -
21
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 -
22
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. -
23
Bifrost
Bifrost AI
Quickly and easily generate diverse and realistic synthetic data and high-fidelity 3D worlds to enhance model performance. Bifrost's platform is the fastest way to generate the high-quality synthetic images that you need to improve ML performance and overcome real-world data limitations. Prototype and test up to 30x faster by circumventing costly and time-consuming real-world data collection and annotation. Generate data to account for rare scenarios underrepresented in real data, resulting in more balanced datasets. Manual annotation and labeling is an error-prone, resource-intensive process. Easily and quickly generate data that is pre-labeled and pixel-perfect. Real-world data can inherit the biases of conditions under which the data was collected, and generate data to solve for these instances. -
24
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 -
25
Symage
Symage
Symage is a synthetic data platform that generates custom, photorealistic image datasets with automated pixel-perfect labeling to support training and improving AI and computer vision models; using physics-based rendering and simulation rather than generative AI, it produces high-fidelity synthetic images that mirror real-world conditions and handle diverse scenarios, lighting, camera angles, object motion, and edge cases with controlled precision, which helps eliminate data bias, reduce manual labeling, and dramatically cut data preparation time by up to 90%. Designed to give teams the right data for model training rather than relying on limited real datasets, Symage lets users tailor environments and variables to match specific use cases, ensuring datasets are balanced, scalable, and accurately labeled at every pixel. It is built on decades of expertise in robotics, AI, machine learning, and simulation, offering a way to overcome data scarcity and boost model accuracy. -
26
Rockfish Data
Rockfish Data
Rockfish Data is the industry's first outcome-centric synthetic data generation platform, unlocking the true value of operational data. Rockfish helps enterprises take advantage of siloed data to train ML/AI workflows, produce compelling datasets for product demos, and more. The platform intelligently adapts to and optimizes diverse datasets, seamlessly adjusting to various data types, sources, and structures for maximum efficiency. It focuses on delivering specific, measurable results that drive tangible business value, with a purpose-built architecture emphasizing robust security measures to ensure data integrity and privacy. By operationalizing synthetic data, Rockfish enables organizations to overcome data silos, enhance machine learning and artificial intelligence workflows, and generate high-quality datasets for various applications. -
27
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. -
28
Synthesis AI
Synthesis AI
A synthetic data platform for ML engineers to enable the development of more capable AI models. Simple APIs provide on-demand generation of perfectly-labeled, diverse, and photoreal images. Highly-scalable cloud-based generation platform delivers millions of perfectly labeled images. On-demand data enables new data-centric approaches to develop more performant models. An expanded set of pixel-perfect labels including segmentation maps, dense 2D/3D landmarks, depth maps, surface normals, and much more. Rapidly design, test, and refine your products before building hardware. Prototype different imaging modalities, camera placements, and lens types to optimize your system. Reduce bias in your models associated with misbalanced data sets while preserving privacy. Ensure equal representation across identities, facial attributes, pose, camera, lighting, and much more. We have worked with world-class customers across many use cases. -
29
Syntho
Syntho
Syntho typically deploys in the safe environment of our customers so that (sensitive) data never leaves the safe and trusted environment of the customer. Connect to the source data and target environment with our out-of-the-box connectors. Syntho can connect with every leading database & filesystem and supports 20+ database connectors and 5+ filesystem connectors. Define the type of synthetization you would like to run, realistically mask or synthesize new values, automatically detect sensitive data types. Utilize and share the protected data securely, ensuring compliance and privacy are maintained throughout its usage. -
30
Privacera
Privacera
At the intersection of data governance, privacy, and security, Privacera’s unified data access governance platform maximizes the value of data by providing secure data access control and governance across hybrid- and multi-cloud environments. The hybrid platform centralizes access and natively enforces policies across multiple cloud services—AWS, Azure, Google Cloud, Databricks, Snowflake, Starburst and more—to democratize trusted data enterprise-wide without compromising compliance with regulations such as GDPR, CCPA, LGPD, or HIPAA. Trusted by Fortune 500 customers across finance, insurance, retail, healthcare, media, public and the federal sector, Privacera is the industry’s leading data access governance platform that delivers unmatched scalability, elasticity, and performance. Headquartered in Fremont, California, Privacera was founded in 2016 to manage cloud data privacy and security by the creators of Apache Ranger™ and Apache Atlas™. -
31
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 -
32
The growing security threats and ever-expanding privacy regulations have made it necessary to limit exposure of sensitive data. Oracle Data Masking and Subsetting helps database customers improve security, accelerate compliance, and reduce IT costs by sanitizing copies of production data for testing, development, and other activities and by easily discarding unnecessary data. Oracle Data Masking and Subsetting enables entire copies or subsets of application data to be extracted from the database, obfuscated, and shared with partners inside and outside of the business. The integrity of the database is preserved assuring the continuity of the applications. Application Data Modeling automatically discovers columns from Oracle Database tables containing sensitive information based on built-in discovery patterns such as national identifiers, credit card numbers, and other personally identifiable information. It also automatically discovers parent-child relationships defined in the database.Starting Price: $230 one-time payment
-
33
Imperva Data Security Fabric
Imperva
Protect data at scale with an enterprise-class, multicloud, hybrid security solution for all data types. Extend data security across multicloud, hybrid, and on-premises environments. Discover and classify structured, semi-structured, & unstructured. Prioritize data risk for both incident context and additional data capabilities. Centralize data management via a single data service or dashboard. Protect against data exposure and avoid breaches. Simplify data-centric security, compliance, and governance. Unify the view and gain insights to at-risk data and users. Supervise Zero Trust posture and policy enforcement. Save time and money with automation and workflows. Support for hundreds of file shares and data repositories including public, private, datacenter and third-party cloud services. Cover both your immediate needs & future integrations as you transform and extend use cases in the cloud. -
34
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. -
35
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. -
36
Libelle DataMasking
Libelle
Libelle DataMasking (LDM) is a robust, enterprise-grade data masking solution that automates the anonymization of sensitive or personal data—such as names, addresses, dates, emails, IBANs, credit cards—and transforms them into realistic, logically consistent substitutes that maintain referential integrity across SAP and non‑SAP systems, including Oracle, SQL Server, IBM DB2, MySQL, PostgreSQL, SAP HANA, flat files, and cloud databases. Capable of processing up to 200,000 entries per second and supporting parallelized masking for massive datasets, LDM uses a multithreaded architecture to efficiently read, anonymize, and write data back with high performance. It features over 40 built‑in anonymization algorithms—such as number, alphanumeric, date shifting, name, email, IBAN masking, credit card obfuscation, and mapping algorithms—as well as templates for SAP modules (CRM, ERP, FI/CO, HCM, SD, SRM). -
37
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. -
38
Lucky Robots
Lucky Robots
Lucky Robots is a robotics-focused simulation platform that lets teams train, test, and refine AI models for robots entirely in high-fidelity virtual environments that mimic real-world physics, sensors, and interactions, enabling massive generation of synthetic training data and rapid iteration without physical robots or costly lab setups. It uses hyper-realistic scenes (e.g., kitchens, terrain) built on advanced simulation tech to create varied edge cases, generate millions of labeled episodes for scalable model learning, and accelerate development while reducing cost and safety risk. It supports natural language control in simulated scenarios, lets users bring their own robot models or choose from commercially available ones, and includes tools for collaboration, environment sharing, and training workflows via LuckyHub, helping developers push models toward real-world performance more efficiently.Starting Price: Free -
39
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. -
40
Urbiverse
Urbiverse
Urbiverse helps you make smarter strategic decisions about urban mobility and logistics with AI‑driven simulations, synthetic data solutions, real‑time what‑if analysis, and optimized fleet sizing and infrastructure planning. It enables operators to forecast demand based on historical data, events, seasonal trends and real‑time analytics; simulate scenarios to determine the impact of new ride‑sharing, bike‑sharing, cargo‑bike or fleet‑size programs on traffic, user satisfaction, environmental goals, profitability and costs; evaluate financial implications under various tender conditions; optimize fleet distribution, operations management and micromobility parking; and combine real‑time and historical data to allocate resources efficiently across different vehicle types, empowering mobility operators and planners to move from guesswork to data‑driven decisions. Urbiverse processes millions of trips, supports infrastructure planning, and empowers urban fleet planners to test scenarios. -
41
Protect your file and database data from misuse and help comply with industry and government regulations with this suite of integrated encryption products. IBM Guardium Data Encryption consists of an integrated suite of products built on a common infrastructure. These highly-scalable solutions provide encryption, tokenization, data masking and key management capabilities to help protect and control access to databases, files and containers across the hybrid multicloud—securing assets residing in cloud, virtual, big data and on-premise environments. Securely encrypting file and database data with such functionalities as tokenization, data masking and key rotation can help organizations address compliance with government and industry regulations, including GDPR, CCPA, PCI DSS and HIPAA. Guardium Data Encryption's capabilities—such as data access audit logging, tokenization, data masking and key management—help meet regulations such as HIPAA, CCPA or GDPR.
-
42
Rendered.ai
Rendered.ai
Overcome challenges in acquiring data for machine learning and AI systems training. Rendered.ai is a PaaS designed for data scientists, engineers, and developers. Generate synthetic datasets for ML/AI training and validation. Experiment with sensor models, scene content, and post-processing effects. Characterize and catalog real and synthetic datasets. Download or move data to your own cloud repositories for processing and training. Power innovation and increase productivity with synthetic data as a capability. Build custom pipelines to model diverse sensors and computer vision inputs. Start quickly with free, customizable Python sample code to model SAR, RGB satellite imagery, and more sensor types. Experiment and iterate with flexible licensing that enables nearly unlimited content generation. Create labeled content rapidly in a hosted, high-performance computing environment. Enable collaboration between data scientists and data engineers with a no-code configuration experience. -
43
OneView
OneView
Working exclusively with real data creates significant challenges for machine learning model training. Synthetic data enables limitless machine learning model training, addressing the drawbacks and challenges of real data. Boost the performance of your geospatial analytics by creating the imagery you need. Customizable satellite, drone, and aerial imagery. Create scenarios, change object ratios, and adjust imaging parameters quickly and iteratively. Any rare objects or occurrences can be created. The resulting datasets are fully-annotated, error-free, and ready for training. The OneView simulation engine creates 3D worlds as the base for synthetic satellite and aerial images, layered with multiple randomization factors, filters, and variation parameters. The synthetic images replace real data for remote sensing systems in machine learning model training. They achieve superior interpretation results, especially in cases with limited coverage or poor-quality data. -
44
Parallel Domain Replica Sim
Parallel Domain
Parallel Domain Replica Sim enables the creation of high-fidelity, fully annotated, simulation-ready environments from users’ own captured data (photos, videos, scans). With PD Replica, you can generate near-pixel-perfect reconstructions of real-world scenes, transforming them into virtual environments that preserve visual detail and realism. PD Sim provides a Python API through which perception, machine learning, and autonomy teams can configure and run large-scale test scenarios and simulate sensor inputs (camera, lidar, radar, etc.) in either open- or closed-loop mode. These simulated sensor feeds come with full annotations, so developers can test their perception systems under a wide variety of conditions, lighting, weather, object configurations, and edge cases, without needing to collect real-world data for every scenario. -
45
Krontech Single Connect
Krontech
Establish a flexible, centrally managed and layered defense security architecture against insider threats with the world's leading Privileged Access Management platform. Single Connect™ Privileged Access Management Suite, known as the fastest to deploy and the most secure PAM solution, delivering IT operational security and efficiency to Enterprises and Telco's globally. Single Connect™ enables IT managers and network admins to efficiently secure the access, control configurations and indisputably record all activities in the data center or network infrastructure, in which any breach in privileged accounts access might have material impact on business continuity. Single Connect™ provides tools, capabilities, indisputable log records and audit trails to help organizations comply with regulations including ISO 27001, ISO 31000: 2009, KVKK, PCI DSS, EPDK, SOX, HIPAA, GDPR in highly regulated industries like finance, energy, health and telecommunications. -
46
Amazon SageMaker Ground Truth
Amazon Web Services
Amazon SageMaker allows you to identify raw data such as images, text files, and videos; add informative labels and generate labeled synthetic data to create high-quality training data sets for your machine learning (ML) models. SageMaker offers two options, Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth, which give you the flexibility to use an expert workforce to create and manage data labeling workflows on your behalf or manage your own data labeling workflows. data labeling. If you want the flexibility to create and manage your own personal and data labeling workflows, you can use SageMaker Ground Truth. SageMaker Ground Truth is a data labeling service that makes data labeling easy and gives you the option of using human annotators via Amazon Mechanical Turk, third-party providers, or your own private staff.Starting Price: $0.08 per month -
47
Randtronics DPM easyData
Randtronics
DPM easyData is a high-performance data spoofing or de-identification engine. Data spoofing examples include masking, tokenization, anonymization, pseudonymization and encryption. DPM data spoofing processes replace whole or parts of sensitive data with a non-sensitive equivalent (creates fake data) and is a very powerful data protection tool. DPM easyData is a software data security solution that allows web and app server applications and databases to tokenize and anonymize data and apply masking policies for unauthorized users when retrieving sensitive data. The software allows a high level of granularity, defining which authorized users have access to which protection policies, and what operations they may perform with those protection policies. DPM easyData is extremely customizable and is able to protect and tokenize many different types of data. The software has been designed to be flexible and users are free to define any format of input data and token format. -
48
MDClone
MDClone
The MDClone ADAMS Platform is a powerful, self-service data analytics environment enabling healthcare collaboration, research, and innovation. Get access to insights in real-time, dynamically, securely, and independently with our pioneering platform that breaks down real barriers in healthcare data exploration. Put your organization on a continuous learning path to improve care, streamline operations, foster research, and drive innovation, ultimately empowering action across your entire healthcare ecosystem. Enable collaboration across teams, organizations, and even external third-parties with the use of synthetic data so they can dive deeper into the information they need when they need it. By accessing real-world data from the source, inside a health system, life science organizations can identify promising patient cohorts for post-marketing analysis. Discover a fundamentally different approach to unlocking healthcare data for life sciences. -
49
Anyverse
Anyverse
A flexible and accurate synthetic data generation platform. Craft the data you need for your perception system in minutes. Design scenarios for your use case with endless variations. Generate your datasets in the cloud. Anyverse offers a scalable synthetic data software platform to design, train, validate, or fine-tune your perception system. It provides unparalleled computing power in the cloud to generate all the data you need in a fraction of the time and cost compared with other real-world data workflows. Anyverse provides a modular platform that enables efficient scene definition and dataset production. Anyverse™ Studio is a standalone graphical interface application that manages all Anyverse functions, including scenario definition, variability settings, asset behaviors, dataset settings, and inspection. Data is stored in the cloud, and the Anyverse cloud engine is responsible for final scene generation, simulation, and rendering. -
50
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
