Alternatives to StreamScape
Compare StreamScape alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to StreamScape in 2026. Compare features, ratings, user reviews, pricing, and more from StreamScape competitors and alternatives in order to make an informed decision for your business.
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Teradata VantageCloud
Teradata
Teradata VantageCloud: The complete cloud analytics and data platform for AI. Teradata VantageCloud is an enterprise-grade, cloud-native data and analytics platform that unifies data management, advanced analytics, and AI/ML capabilities in a single environment. Designed for scalability and flexibility, VantageCloud supports multi-cloud and hybrid deployments, enabling organizations to manage structured and semi-structured data across AWS, Azure, Google Cloud, and on-premises systems. It offers full ANSI SQL support, integrates with open-source tools like Python and R, and provides built-in governance for secure, trusted AI. VantageCloud empowers users to run complex queries, build data pipelines, and operationalize machine learning models—all while maintaining interoperability with modern data ecosystems. -
2
DataBahn
DataBahn
DataBahn.ai is redefining how enterprises manage the explosion of security and operational data in the AI era. Our AI-powered data pipeline and fabric platform helps organizations securely collect, enrich, orchestrate, and optimize enterprise data—including security, application, observability, and IoT/OT telemetry—for analytics, automation, and AI. With native support for over 400 integrations and built-in enrichment capabilities, DataBahn streamlines fragmented data workflows and reduces SIEM and infrastructure costs from day one. The platform requires no specialist training, enabling security and IT teams to extract insights in real time and adapt quickly to new demands. We've helped Fortune 500 and Global 2000 companies reduce data processing costs by over 50% and automate more than 80% of their data engineering workloads. -
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Tenzir
Tenzir
Tenzir is a data pipeline engine specifically designed for security teams, facilitating the collection, transformation, enrichment, and routing of security data throughout its lifecycle. It enables users to seamlessly gather data from various sources, parse unstructured data into structured formats, and transform it as needed. It optimizes data volume, reduces costs, and supports mapping to standardized schemas like OCSF, ASIM, and ECS. Tenzir ensures compliance through data anonymization features and enriches data by adding context from threats, assets, and vulnerabilities. It supports real-time detection and stores data efficiently in Parquet format within object storage systems. Users can rapidly search and materialize necessary data and reactivate at-rest data back into motion. Tension is built for flexibility, allowing deployment as code and integration into existing workflows, ultimately aiming to reduce SIEM costs and provide full control. -
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Cribl Stream
Cribl
Cribl Stream allows you to implement an observability pipeline which helps you parse, restructure, and enrich data in flight - before you pay to analyze it. Get the right data, where you want, in the formats you need. Route data to the best tool for the job - or all the tools for the job - by translating and formatting data into any tooling schema you require. Let different departments choose different analytics environments without having to deploy new agents or forwarders. As much as 50% of log and metric data goes unused – null fields, duplicate data, and fields that offer zero analytical value. With Cribl Stream, you can trim wasted data streams and analyze only what you need. Cribl Stream is the best way to get multiple data formats into the tools you trust for your Security and IT efforts. Use the Cribl Stream universal receiver to collect from any machine data source - and even to schedule batch collection from REST APIs, Kinesis Firehose, Raw HTTP, and Microsoft Office 365 APIsStarting Price: Free (1TB / Day) -
5
Databricks Data Intelligence Platform
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
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Gathr.ai
Gathr.ai
Gathr is a Data+AI fabric, helping enterprises rapidly deliver production-ready data and AI products. Data+AI fabric enables teams to effortlessly acquire, process, and harness data, leverage AI services to generate intelligence, and build consumer applications— all with unparalleled speed, scale, and confidence. Gathr’s self-service, AI-assisted, and collaborative approach enables data and AI leaders to achieve massive productivity gains by empowering their existing teams to deliver more valuable work in less time. With complete ownership and control over data and AI, flexibility and agility to experiment and innovate on an ongoing basis, and proven reliable performance at real-world scale, Gathr allows them to confidently accelerate POVs to production. Additionally, Gathr supports both cloud and air-gapped deployments, making it the ideal choice for diverse enterprise needs. Gathr, recognized by leading analysts like Gartner and Forrester, is a go-to-partner for Fortune 500Starting Price: $0.25/credit -
7
Dagster
Dagster Labs
Dagster is a next-generation orchestration platform for the development, production, and observation of data assets. Unlike other data orchestration solutions, Dagster provides you with an end-to-end development lifecycle. Dagster gives you control over your disparate data tools and empowers you to build, test, deploy, run, and iterate on your data pipelines. It makes you and your data teams more productive, your operations more robust, and puts you in complete control of your data processes as you scale. Dagster brings a declarative approach to the engineering of data pipelines. Your team defines the data assets required, quickly assessing their status and resolving any discrepancies. An assets-based model is clearer than a tasks-based one and becomes a unifying abstraction across the whole workflow.Starting Price: $0 -
8
DataKitchen
DataKitchen
Reclaim control of your data pipelines and deliver value instantly, without errors. The DataKitchen™ DataOps platform automates and coordinates all the people, tools, and environments in your entire data analytics organization – everything from orchestration, testing, and monitoring to development and deployment. You’ve already got the tools you need. Our platform automatically orchestrates your end-to-end multi-tool, multi-environment pipelines – from data access to value delivery. Catch embarrassing and costly errors before they reach the end-user by adding any number of automated tests at every node in your development and production pipelines. Spin-up repeatable work environments in minutes to enable teams to make changes and experiment – without breaking production. Fearlessly deploy new features into production with the push of a button. Free your teams from tedious, manual work that impedes innovation. -
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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. -
10
Dataform
Google
Dataform enables data analysts and data engineers to develop and operationalize scalable data transformation pipelines in BigQuery using only SQL from a single, unified environment. Its open source core language lets teams define table schemas, configure dependencies, add column descriptions, and set up data quality assertions within a shared code repository while applying software development best practices, version control, environments, testing, and documentation. A fully managed, serverless orchestration layer automatically handles workflow dependencies, tracks lineage, and executes SQL pipelines on demand or via schedules in Cloud Composer, Workflows, BigQuery Studio, or third-party services. In the browser-based development interface, users get real-time error feedback, visualize dependency graphs, connect to GitHub or GitLab for commits and code reviews, and launch production-grade pipelines in minutes without leaving BigQuery Studio.Starting Price: Free -
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Upsolver
Upsolver
Upsolver makes it incredibly simple to build a governed data lake and to manage, integrate and prepare streaming data for analysis. Define pipelines using only SQL on auto-generated schema-on-read. Easy visual IDE to accelerate building pipelines. Add Upserts and Deletes to data lake tables. Blend streaming and large-scale batch data. Automated schema evolution and reprocessing from previous state. Automatic orchestration of pipelines (no DAGs). Fully-managed execution at scale. Strong consistency guarantee over object storage. Near-zero maintenance overhead for analytics-ready data. Built-in hygiene for data lake tables including columnar formats, partitioning, compaction and vacuuming. 100,000 events per second (billions daily) at low cost. Continuous lock-free compaction to avoid “small files” problem. Parquet-based tables for fast queries. -
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Teradata QueryGrid
Teradata
Deploying multiple analytic engines means best-fit engineering, so QueryGrid lets users leverage the right tool for the job. SQL is the language of business, and QueryGrid delivers unparalleled SQL access across commercial and open source analytical engines. Built for a hybrid multi-cloud reality, Vantage solves the world’s most complex data challenges at scale. Software that delivers autonomy, visibility, and insights to keep pace with changing customer demand. -
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Nexla
Nexla
Nexla's AI Integration platform helps enterprises accelerate data onboarding across any connector, format, or schema, breaking silos and enabling production-grade AI with Data Products and agentic retrieval without coding overhead. Leading companies, including Autodesk, Carrier, DoorDash, Instacart, Johnson & Johnson, LinkedIn, and LiveRamp trust Nexla to power mission-critical data operations across diverse environments. With flexible deployment across cloud, hybrid, and on-premises environments, Nexla meets enterprise-grade security and compliance requirements including SOC 2 Type II, GDPR, CCPA, and HIPAA. Nexla delivers 10x faster implementation than traditional alternatives, turning data challenges into competitive advantage.Starting Price: $1000/month -
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Ingestro
Ingestro
Ingestro is an enterprise-grade, AI-powered data import solution designed to help software companies clean, validate, and onboard customer data faster. It supports uploads from a wide variety of formats—including CSV, Excel, XML, JSON, and even PDFs—while automatically mapping, cleaning, and restructuring the data to match each company’s schema. With its Data Importer SDK and Data Pipelines, Ingestro enables teams to offer a seamless self-serve import experience without building in-house tools. The platform improves scalability by automating recurring data onboarding tasks, reducing dependency on developers, and accelerating customer time-to-value. Companies rely on Ingestro to process billions of records securely thanks to features like ISO 27001 certification, GDPR compliance, and optional self-hosting. By transforming tedious data imports into smooth, AI-enhanced workflows, Ingestro helps product, engineering, and customer success teams reclaim valuable time. -
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PartiQL
PartiQL
PartiQL's extensions to SQL are easy to understand, treat nested data as first class citizens and compose seamlessly with each other and SQL. This enables intuitive filtering, joining and aggregation on the combination of structured, semistructured and nested datasets. PartiQL enables unified query access across multiple data stores and data formats by separating the syntax and semantics of a query from the underlying format of the data or the data store that is being accessed. It enables users to interact with data with or without regular schema. PartiQL syntax, semantics, the embeddable reference interpreter, CLI, test framework, and tests are licensed under the Apache License, version 2.0, allowing you to freely use, copy, and distribute your changes under the terms of your choice. -
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Zetaris
Zetaris
Rather than uploading the data to a central place to analyze it, Zetaris enables instant analytics across all your data, now. This means you can connect multiple databases and analyze them together in real-time, without the time and cost (and fail rate) associated with moving the data to a central location. Our unique analytical query optimizer ensures speed and scalability for whatever query is being run, across any combination of data sources. Ensure data governance and security by not moving data, and analyzing it at its source. Don't move the data. No data extraction, no data transformation, no copying of data to another repository. Remove unnecessary storage, processing and support costs, thanks to zero data duplication. -
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Data Taps
Data Taps
Build your data pipelines like Lego blocks with Data Taps. Add new metrics layers, zoom in, and investigate with real-time streaming SQL. Build with others, share and consume data, globally. Refine and update without hassle. Use multiple models/schemas during schema evolution. Built to scale with AWS Lambda and S3. -
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Anzo
Cambridge Semantics
Anzo is a modern data discovery and integration platform that lets anyone find, connect and blend any enterprise data into analytics-ready datasets. Anzo’s unique use of semantics and graph data models makes it practical for the first time for virtually anyone in your organization – from skilled data scientists to novice business users – to drive the data discovery and integration process and build their own analytics-ready datasets. Anzo’s graph data models provide business users with a visual map of enterprise data that is easy to understand and navigate, even when your data is vast, siloed and complex. Semantics add business content to data, allowing users to harmonize data based on shared definitions and build blended, business-ready data on demand. -
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Denodo
Denodo Technologies
The core technology to enable modern data integration and data management solutions. Quickly connect disparate structured and unstructured sources. Catalog your entire data ecosystem. Data stays in the sources and it is accessed on demand, with no need to create another copy. Build data models that suit the needs of the consumer, even across multiple sources. Hide the complexity of your back-end technologies from the end users. The virtual model can be secured and consumed using standard SQL and other formats like REST, SOAP and OData. Easy access to all types of data. Full data integration and data modeling capabilities. Active Data Catalog and self-service capabilities for data & metadata discovery and data preparation. Full data security and data governance capabilities. Fast intelligent execution of data queries. Real-time data delivery in any format. Ability to create data marketplaces. Decoupling of business applications from data systems to facilitate data-driven strategies. -
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Crux
Crux
Find out why the heavy hitters are using the Crux external data automation platform to scale external data integration, transformation, and observability without increasing headcount. Our cloud-native data integration technology accelerates the ingestion, preparation, observability and ongoing delivery of any external dataset. The result is that we can ensure you get quality data in the right place, in the right format when you need it. Leverage automatic schema detection, delivery schedule inference, and lifecycle management to build pipelines from any external data source quickly. Enhance discoverability throughout your organization through a private catalog of linked and matched data products. Enrich, validate, and transform any dataset to quickly combine it with other data sources and accelerate analytics. -
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Open mHealth
Open mHealth
Data schemas specify the format and content of data, such as blood glucose readings, which affects how software programs process that data. Systems often must handle data coming from many different devices or platforms, with each source describing the data differently. It is much easier to process and make sense of data if all data points for a specific measure (e.g. blood glucose) are expressed in a shared, common schema, regardless of where the data came from. A common schema serves as a single source of documentation that can be referenced whenever and wherever the data points are used. In healthcare, common data schemas are particularly important because of the semantic importance and complexity of health data. For example, the distinction between fasting and non-fasting blood glucose is critical to its clinical meaning. -
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JSONBuddy
JSONBuddy
JSONBuddy is a comprehensive JSON editor and validator designed to streamline the creation and management of JSON and JSON Schema files. It offers a range of features, including a text editor with syntax coloring, auto-completion, and code folding, as well as a grid-style editor that simplifies the process of building JSON structures. It ensures error-free JSON through built-in syntax checking and validation against JSON Schema standards, supporting Drafts 4, 6, 7, 2019-09, and 2020-12. Additionally, JSONBuddy provides functionalities for converting between JSON, XML, and CSV formats, importing CSV data to generate JSON, and generating HTML documentation from JSON Schemas. For large JSON files, it offers robust support, allowing users to open, navigate, and edit files with thousands or even millions of lines efficiently.Starting Price: $39 one-time payment -
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Querona
YouNeedIT
We make BI & Big Data analytics work easier and faster. Our goal is to empower business users and make always-busy business and heavily loaded BI specialists less dependent on each other when solving data-driven business problems. If you have ever experienced a lack of data you needed, time to consuming report generation or long queue to your BI expert, consider Querona. Querona uses a built-in Big Data engine to handle growing data volumes. Repeatable queries can be cached or calculated in advance. Optimization needs less effort as Querona automatically suggests query improvements. Querona empowers business analysts and data scientists by putting self-service in their hands. They can easily discover and prototype data models, add new data sources, experiment with query optimization and dig in raw data. Less IT is needed. Now users can get live data no matter where it is stored. If databases are too busy to be queried live, Querona will cache the data. -
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EraSearch
Era Software
Purpose-built for cloud-native deployments, EraSearch brings you a dynamic data fabric that leverages decoupled storage & compute, a true zero-schema design, and adaptive indexing to deliver an infinitely-scalable log management experience with an unparalleled reduction in cost and complexity. Lots of log management products are built on top of Elasticsearch. We built EraSearch from scratch to solve its key problems. By embracing a stateless design for all of the core components, managing EraSearch with k8s is a dream. Lots of log management products are built on top of Elasticsearch. We built EraSearch from scratch to solve its key problems. By using a modern, coordination-free ingest design, EraSearch can handle data at a greatly-reduced cost. Running EraSearch is completely hands-off, so you never have to worry about cluster health again.Starting Price: ¢65 per GB -
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Postbird
Paxa
Postbird is a cross-platform PostgreSQL GUI client, written in JavaScript, and runs with Electron. Supports views, material views, foreign tables, constraints, and schemas, and connects to Heroku's Postgres. Can manage extensions, procedures, users, filter tables, edit values, and import & export tables or databases. Have comfortable query editing with saving the last query, syntax highlighting, keyboard shortcuts, search, snippets, query history, viewing large results, explaining formatting, and saving results as CSV.Starting Price: Free -
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Atlan
Atlan
The modern data workspace. Make all your data assets from data tables to BI reports, instantly discoverable. Our powerful search algorithms combined with easy browsing experience, make finding the right asset, a breeze. Atlan auto-generates data quality profiles which make detecting bad data, dead easy. From automatic variable type detection & frequency distribution to missing values and outlier detection, we’ve got you covered. Atlan takes the pain away from governing and managing your data ecosystem! Atlan’s bots parse through SQL query history to auto construct data lineage and auto-detect PII data, allowing you to create dynamic access policies & best in class governance. Even non-technical users can directly query across multiple data lakes, warehouses & DBs using our excel-like query builder. Native integrations with tools like Tableau and Jupyter makes data collaboration come alive. -
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Sonic XML Server
Progress Technologies
Sonic XML Server ™ is a set of high-speed processing, storage and query services for XML documents required to manage Sonic ESB operational data. By processing XML messages in native XML format, XML Server is very fast and does not place restrictions on the XML message schema. The advent of Extensible Markup Language (XML), a true hardware and software independent data format, was a revolutionary step forward. Because XML describes information independently of a specific system or application data formatting rules, XML is a key technology for supporting flexible exchange of heterogeneous data. However, this flexibility can take a lot of time and resources to process the XML format. Sonic XML Server provides fast processing of operational data and storage of XML messages required to efficiently implement a service-oriented architecture. Sonic XML Server extends and enhances Sonic ESB's XML message processing model by providing native query, storage and processing services. -
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QuerySurge
RTTS
QuerySurge leverages AI to automate the data validation and ETL testing of Big Data, Data Warehouses, Business Intelligence Reports and Enterprise Apps/ERPs with full DevOps functionality for continuous testing. Use Cases - Data Warehouse & ETL Testing - Hadoop & NoSQL Testing - DevOps for Data / Continuous Testing - Data Migration Testing - BI Report Testing - Enterprise App/ERP Testing QuerySurge Features - Projects: Multi-project support - AI: automatically create datas validation tests based on data mappings - Smart Query Wizards: Create tests visually, without writing SQL - Data Quality at Speed: Automate the launch, execution, comparison & see results quickly - Test across 200+ platforms: Data Warehouses, Hadoop & NoSQL lakes, databases, flat files, XML, JSON, BI Reports - DevOps for Data & Continuous Testing: RESTful API with 60+ calls & integration with all mainstream solutions - Data Analytics & Data Intelligence: Analytics dashboard & reports -
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Apache Avro
Apache Software Foundation
Apache Avro™ is a data serialization system. Avro provides rich data structures, a compact, fast, binary data format, a container file, to store persistent data, remote procedure call (RPC). Also, it provides simple integration with dynamic languages. Code generation is not required to read or write data files nor to use or implement RPC protocols. Code generation as an optional optimization, only worth implementing for statically typed languages. Avro relies on schemas. When Avro data is read, the schema used when writing it is always present. This permits each datum to be written with no per-value overheads, making serialization both fast and small. This also facilitates use with dynamic, scripting languages, since data, together with its schema, is fully self-describing. When Avro data is stored in a file, its schema is stored with it, so that files may be processed later by any program. If the program reading the data expects a different schema this can be easily resolved. -
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Qlik Compose
Qlik
Qlik Compose for Data Warehouses provides a modern approach by automating and optimizing data warehouse creation and operation. Qlik Compose automates designing the warehouse, generating ETL code, and quickly applying updates, all whilst leveraging best practices and proven design patterns. Qlik Compose for Data Warehouses dramatically reduces the time, cost and risk of BI projects, whether on-premises or in the cloud. Qlik Compose for Data Lakes automates your data pipelines to create analytics-ready data sets. By automating data ingestion, schema creation, and continual updates, organizations realize faster time-to-value from their existing data lake investments. -
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tap
Digital Society
Turn spreadsheets and data files into production-ready APIs without writing backend code. Upload CSV, JSONL, Parquet and other formats, clean and join them with familiar SQL, and expose secure, documented endpoints instantly. Built-in features include auto-generated OpenAPI docs, API key security, geospatial filters with H3 indexing, usage monitoring, and high-performance queries. You can also download transformed datasets anytime to avoid vendor lock-in. Works for single files, combined datasets, or public data portals with minimal setup. Key features - Create secure, documented APIs directly from CSV, JSONL, and Parquet. - Run familiar SQL queries to clean, join, and enrich data. - No backend setup or servers to configure or maintain. - Auto-generated OpenAPI documentation for every endpoint you create. - Secure endpoints with API keys and isolated storage for safety. - Geospatial filters, H3 indexing, and fast, optimised queries at scale.Starting Price: $10/month -
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Serverless, interactive querying for analyzing data in IBM Cloud Object Storage. Query your data directly where it is stored, there's no ETL, no databases, and no infrastructure to manage. IBM Cloud SQL Query uses Apache Spark, an open-source, fast, extensible, in-memory data processing engine optimized for low latency and ad hoc analysis of data. No ETL or schema definition needed to enable SQL queries. Analyze data where it sits in IBM Cloud Object Storage using our query editor and REST API. Run as many queries as you need; with pay-per-query pricing, you pay only for the data scan. Compress or partition data to drive savings and performance. IBM Cloud SQL Query is highly available and executes queries using compute resources across multiple facilities. IBM Cloud SQL Query supports a variety of data formats such as CSV, JSON and Parquet, and allows for standard ANSI SQL.Starting Price: $5.00/Terabyte-Month
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Osmos
Osmos
With Osmos, your customers can easily clean their messy data files and import them directly into your operational system without writing a line of code. At the core, we have an AI-powered data transformation engine that enables users to map, validate, and clean data with only a few clicks. Your account will be charged or credited based on the percentage of the billing cycle left at the time the plan was changed. An eCommerce company automates ingestion of product catalog data from multiple distributors and vendors into their database. A manufacturing company automates the data ingestion of purchase orders from email attachments into Netsuite. Automatically clean up and reformat incoming data to match your destination schema. Never deal with custom scripts and spreadsheets again.Starting Price: $299 per month -
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Dropbase
Dropbase
Centralize offline data, import files, process and clean up data. Export to a live database with 1 click. Streamline data workflows. Centralize offline data and make it accessible to your team. Bring offline files to Dropbase. Multiple formats. Any way you like. Process and format data. Add, edit, re-order, and delete processing steps. 1-click exports. Export to database, endpoints, or download code with 1 click. Instant REST API access. Query Dropbase data securely with REST API access keys. Onboard data where you need it. Combine and process datasets to fit the desired format or data model. No code. Process your data pipelines using a spreadsheet interface. Track every step. Flexible. Use a library of pre-built processing functions. Or write your own. 1-click exports. Export to database or generate endpoints with 1 click. Manage databases. Manage and databases and credentials.Starting Price: $19.97 per user per month -
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SAP Datasphere
SAP
SAP Datasphere is a unified data experience platform within SAP Business Data Cloud, designed to provide seamless, scalable access to mission-critical business data. It integrates data from SAP and non-SAP systems, harmonizing diverse data landscapes and enabling faster, more accurate decision-making. With capabilities like data federation, cataloging, semantic modeling, and real-time data integration, SAP Datasphere ensures that businesses have consistent, contextualized data across hybrid and cloud environments. The platform simplifies data management by preserving business context and logic, providing a comprehensive view of data that drives innovation and enhances business processes. -
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Liquid Studio
Liquid Technologies
Liquid Studio provides an advanced toolkit for XML and JSON development along with Web Service Testing and Data Mapping and Data Transformation tools. The Development Environment contains a complete set of tools for designing XML and JSON data structures and schemas. These tools provide editing, validating and advanced transformation capabilities. For novice or expert, the intuitive interface and comprehensive features will help you save time and money delivering a successful project. Visualize and edit an abstracted view of your XML schema(XSD) using an intuitive user interface, and validate your XSD against the W3C standards.Includes split graphical and text views, intellisense, syntax highlighting, drag and drop, copy and paste, and multi-step undo/redo. Visualize and edit an abstracted view of your JSON schema using an intuitive user interface, and validate your JSON Schema against the IETF standards.Starting Price: $149 one-time payment -
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Axoflow
Axoflow
Axoflow, the Security Data Layer is the foundation for your SIEM and analytics tools enabling the use of AI, up to 70% faster investigations, and more than 50% reduction in SIEM spend by feeding them with actionable data. Axoflow Platform is built up of the following parts: A pipeline acting as the transportation layer for your security data and also acting as an automated ‘translator’ between data schemas. AI - If you prefer to run your detection content locally - whether it’s an AI or ML model, a threat intel lookup, or another type of enrichment - we’ve got you covered. Storage solutions to facilitate the cost-effective storage of security data and also acting as local storage to run your decentralized detection. Orchestration to weave all of the parts together in an easy-to-use GUI that lets youmonitor and manage, and control and search your data. -
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Adaptigent
Adaptigent
Fabric enables you to connect your modern IT ecosystem with your core mission-critical data and transaction systems in a seamless, rapid fashion. We live in a complex world, and our IT systems reflect that complexity. After years or even decades of evolution, market changes, technology shifts, and mergers & acquisitions, CIOs have been left with a level of systems complexity that is often untenable. This complexity not only ties up a huge portion of IT budgets, but it leaves IT organizations struggling to support the real-time needs of the business. No one can eliminate this complexity overnight, but Adaptigent’s Adaptive Integration Fabric can shield your business from the complexity of your mission critical data sources, allowing you to unlock the full potential of the most secure, stable and data rich legacy systems forming the backbone of your organization. -
39
Datazoom
Datazoom
Improving the experience, efficiency, and profitability of streaming video requires data. Datazoom enables video publishers to better operate distributed architectures through centralizing, standardizing, and integrating data in real-time to create a more powerful data pipeline and improve observability, adaptability, and optimization solutions. Datazoom is a video data platform that continually gathers data from endpoints, like a CDN or a video player, through an ecosystem of collectors. Once the data is gathered, it is normalized using standardized data definitions. This data is then sent through available connectors to analytics platforms like Google BigQuery, Google Analytics, and Splunk and can be visualized in tools such as Looker and Superset. Datazoom is your key to a more effective and efficient data pipeline. Get the data you need in real-time. Don’t wait for your data when you need to resolve an issue immediately. -
40
Arcion
Arcion Labs
Deploy production-ready change data capture pipelines for high-volume, real-time data replication - without a single line of code. Supercharged Change Data Capture. Enjoy automatic schema conversion, end-to-end replication, flexible deployment, and more with Arcion’s distributed Change Data Capture (CDC). Leverage Arcion’s zero data loss architecture for guaranteed end-to-end data consistency, built-in checkpointing, and more without any custom code. Leave scalability and performance concerns behind with a highly-distributed, highly parallel architecture supporting 10x faster data replication. Reduce DevOps overhead with Arcion Cloud, the only fully-managed CDC offering. Enjoy autoscaling, built-in high availability, monitoring console, and more. Simplify & standardize data pipelines architecture, and zero downtime workload migration from on-prem to cloud.Starting Price: $2,894.76 per month -
41
Currents News API
Currents News API
Currents News API transforms global news into a developer-friendly service by ingesting over 90,000 articles daily from 70 countries in 18 languages and maintaining a four-year archive of more than 26 million items, all parsed into structured JSON via its in-house ExtractNet deep-learning extractor. It monitors 43,552 domains to ensure comprehensive coverage, offers natural-language and SQL-like query syntax for precise keyword or phrase searches, and provides built-in analysis tools to surface insights and trends. With a guaranteed 99.9 % SLA, CORS support for browser-based clients, and no need to maintain crawlers, Currents handles data sourcing and endpoint management, delivering news with full content, diverse viewpoints, and proprietary metadata scores. Accessible via simple RESTful endpoints or API calls, it lets users filter by language, region, and topic, compare perspectives across political and cultural spectra, and integrate real-time and historical news into applications. -
42
Datastreamer
Datastreamer
Integrate unstructured external data into your organization in minutes. Datastreamer is a turnkey data platform to source, unify, and enrich unstructured external data with 95% less work than building pipelines in-house. Customers use Datastreamer to feed specialized AI models and accelerate insights in Threat Intelligence, KYC/AML, Financial Analysis and more. Feed your analytics products or specialized AI models with billions of data pieces from social media, blogs, news, forums, dark web data, and more. Our platform unifies source data into a common schema so you can use content from multiple sources simultaneously. Leverage our pre-integrated data partners or connect data from any data supplier. Tap into our powerful AI models to enhance data with components like sentiment analysis and PII redaction. Scale data pipelines with less costs by plugging into our managed infrastructure that is optimized to handle massive volumes of text data. -
43
Gravity Data
Gravity
Gravity's mission is to make streaming data easy from over 100 sources while only paying for what you use. Gravity removes the reliance on engineering teams to deliver streaming pipelines with a simple interface to get streaming up and running in minutes from databases, event data and APIs. Everyone in the data team can now build with simple point and click so that you can focus on building apps, services and customer experiences. Full Execution trace and detailed error messaging for quick diagnosis and resolution. We have implemented new, feature-rich ways for you to quickly get started. From bulk set-up, default schemas and data selection to different job modes and statuses. Spend less time wrangling with infrastructure and more time analysing data while allowing our intelligent engine to keep your pipelines running. Gravity integrates with your systems for notifications and orchestration. -
44
Studio 3T
Studio 3T
Auto-complete queries in a built-in mongo shell that highlights syntax errors as you type and saves your query history. Perfect for MongoDB beginners, a time-saver for pros. Use a drag-and-drop UI to build complex find() queries and filter array elements. Break down aggregation queries into manageable steps and build them stage by stage, for easier debugging and querying. Generate instant code in JavaScript (Node.js), Java (2.x and 3.x driver API), Python, C#, PHP, and Ruby from MongoDB and SQL queries that you can copy and paste into your application. Save MongoDB imports, exports, data comparisons, and migrations as tasks that you can run on demand. Or even better, skip the reminders and schedule them to run exactly when you need them. Make changes to your collection’s schema in just a few clicks, perfect for schema performance tuning, restructuring, or cleaning up after data migration.Starting Price: $499/year/user -
45
RaptorXML Server
Altova
In today’s organizations, Big Data trends and XBRL mandates are producing huge, ever increasing amounts of XML, XBRL, JSON, and Avro data. Now, there is finally a modern, hyper-fast engine to validate, process, transform, and query it all. RaptorXML provides strict conformance with all relevant XML, XBRL, and JSON standards and is continuously submitted to rigorous regression and conformance testing against Altova’s substantial in-house collection of conformance and test suites, as well as industry test suites and customer use-cases. JSON popularity is ever rising, and alongside it the requirement to ensure validity of transacted data. RaptorXML has you covered with JSON syntax checking, JSON validation, JSON Schema validation.Starting Price: €400 one-time payment -
46
JSON Crack
ToDiagram
JSON Crack is an open source tool that transforms complex data formats, including JSON, YAML, CSV, XML, and TOML, into interactive, visually intuitive graphs, enhancing data comprehension and analysis. Users can input data directly, upload files, or provide URLs, and it automatically generates a visual tree graph. It supports data conversion between formats, such as JSON to CSV or XML to JSON, and includes features like JSON formatting, validation, and code generation for TypeScript interfaces, Golang structs, and JSON Schemas. Advanced tools are available for decoding JWTs, executing JQ queries, and performing JSON Path commands. Users can export visualizations as PNG, JPEG, or SVG files. All data processing occurs locally on the user's device, ensuring data privacy. Starting Price: Free -
47
Yandex Data Proc
Yandex
You select the size of the cluster, node capacity, and a set of services, and Yandex Data Proc automatically creates and configures Spark and Hadoop clusters and other components. Collaborate by using Zeppelin notebooks and other web apps via a UI proxy. You get full control of your cluster with root permissions for each VM. Install your own applications and libraries on running clusters without having to restart them. Yandex Data Proc uses instance groups to automatically increase or decrease computing resources of compute subclusters based on CPU usage indicators. Data Proc allows you to create managed Hive clusters, which can reduce the probability of failures and losses caused by metadata unavailability. Save time on building ETL pipelines and pipelines for training and developing models, as well as describing other iterative tasks. The Data Proc operator is already built into Apache Airflow.Starting Price: $0.19 per hour -
48
Pandio
Pandio
Connecting systems to scale AI initiatives is complex, expensive, and prone to fail. Pandio’s cloud-native managed solution simplifies your data pipelines to harness the power of AI. Access your data from anywhere at any time in order to query, analyze, and drive to insight. Big data analytics without the big cost. Enable data movement seamlessly. Streaming, queuing and pub-sub with unmatched throughput, latency, and durability. Design, train, and deploy machine learning models locally in less than 30 minutes. Accelerate your path to ML and democratize the process across your organization. And it doesn’t require months (or years) of disappointment. Pandio’s AI-driven architecture automatically orchestrates your models, data, and ML tools. Pandio works with your existing stack to accelerate your ML initiatives. Orchestrate your models and messages across your organization.Starting Price: $1.40 per hour -
49
Nextflow
Seqera Labs
Data-driven computational pipelines. Nextflow enables scalable and reproducible scientific workflows using software containers. It allows the adaptation of pipelines written in the most common scripting languages. Its fluent DSL simplifies the implementation and deployment of complex parallel and reactive workflows on clouds and clusters. Nextflow is built around the idea that Linux is the lingua franca of data science. Nextflow allows you to write a computational pipeline by making it simpler to put together many different tasks. You may reuse your existing scripts and tools and you don't need to learn a new language or API to start using it. Nextflow supports Docker and Singularity containers technology. This, along with the integration of the GitHub code-sharing platform, allows you to write self-contained pipelines, manage versions, and rapidly reproduce any former configuration. Nextflow provides an abstraction layer between your pipeline's logic and the execution layer.Starting Price: Free -
50
AtScale
AtScale
AtScale helps accelerate and simplify business intelligence resulting in faster time-to-insight, better business decisions, and more ROI on your Cloud analytics investment. Eliminate repetitive data engineering tasks like curating, maintaining and delivering data for analysis. Define business definitions in one location to ensure consistent KPI reporting across BI tools. Accelerate time to insight from data while efficiently managing cloud compute costs. Leverage existing data security policies for data analytics no matter where data resides. AtScale’s Insights workbooks and models let you perform Cloud OLAP multidimensional analysis on data sets from multiple providers – with no data prep or data engineering required. We provide built-in easy to use dimensions and measures to help you quickly derive insights that you can use for business decisions.
