TerminusDB Alternatives

xtendr unhides detailed, privacy-preserving insights across multiple independent data sources. xtendr enables access to thus far inaccessible data, and protects you during your entire data lifecycle, giving you confidence in complete privacy and regulatory compliance. xtendr is more than anonymity, it’s the critical missing piece for multi-party data sharing with true privacy protection - it is cryptography on duty so you can reach your full potential. The most advanced privacy-enhancing data collaboration technology. xtendr solved the decades-long cryptography challenge of data sharing between mutually mistrustful parties. Take your business further with an enterprise-grade data protection offering that allows individual organizations to form data partnerships while protecting sensitive data. Data is the currency of our digital age. Some argue that it is replacing oil as the world's most valuable resource and there is no doubt about its growing importance.

Gigasheet is the big data spreadsheet that requires no set up, training, database or coding skills. If you can use a spreadsheet, you can find opportunities in big data. Best of all, your first 3GB are free! Use Gigasheet to filter, sort, group and aggregate data to gain insights. Create pivot tables by simply dragging columns around. Data cleanup tools and functions clean and insert data during analysis. Enrichments such as Email Validation and Geo IP Location look up make your data even more useful. Sharing and collaboration tools make distributing huge data sets a snap. Gigasheet integrates with more than 135 SaaS platforms and databases. Thousands of individuals and teams use Gigasheet to gain insights in minutes, not hours or days. You don't need to be a data scientist to get answers from big data.

The graph database built for super large-scale graphs with milliseconds of latency. We are continuing to collaborate with the community to prepare, popularize and promote the graph database. Nebula Graph only allows authenticated access via role-based access control. Nebula Graph supports multiple storage engine types and the query language can be extended to support new algorithms. Nebula Graph provides low latency read and write , while still maintaining high throughput to simplify the most complex data sets. With a shared-nothing distributed architecture , Nebula Graph offers linear scalability. Nebula Graph's SQL-like query language is easy to understand and powerful enough to meet complex business needs. With horizontal scalability and a snapshot feature, Nebula Graph guarantees high availability even in case of failures. Large Internet companies like JD, Meituan, and Xiaohongshu have deployed Nebula Graph in production environments.

KgBase, or Knowledge Graph Base, is a collaborative, robust database with versioning, analytics & visualizations. With KgBase, any community or individual can create knowledge graphs to build insights about their data. Import your CSVs and spreadsheets, or use our API to work on data together. Build no-code knowledge graphs with KgBase, our easy-to-use UI lets you traverse the graph, show the results as tables and charts, and much more. Play with your graph data. Build your query and see results update in real time. It's like writing query code in Cypher or Gremlin, except easier. And fast. Your graph can be viewed as a table, allowing you to browse all results - no matter the size. KgBase works great with large graphs (millions of nodes), as well as simple projects. In the cloud, or self-hosted, with wide database support. Introduce graphs into your organization by seeding graph from a template. Results of any query can be easily turned into a chart visualization.

The Only Table That Unifies Your Distributed Operations Data RowShare is a collaborative tool that simplifies and automates data collection and analysis. Make better decisions based on reliable data and real-time insights. Collaborate within your team or with your external stakeholders. • Collect and Share Structured Data Invite users inside or outside your company to read or enter data according to your desired data structure. • Analyze and Visualize Data Turn your data into up-to-date dynamic charts and automatic pivot tables. • Receive and Send Notifications Remind users who have not yet entered their data and be notified when they do. • Control Data Access Take advantage of automated fine-grained permissions to ensure that every user accesses only the relevant data rows and columns. • Ready and Easy to Use • Automatically Generate Documents Generate documents based on a custom document template and the information gathered in your tables.

Coginiti, the AI-enabled enterprise data workspace, empowers everyone to get consistent answers fast to any business question. Accelerating the analytic development lifecycle from development to certification, Coginiti makes it easy for you to search and find approved metrics for your use case. Coginiti integrates all the functionality you need to build, approve, version, and curate analytics across all business domains for reuse, all while adhering to your data governance policy and standards. Data and analytic teams in the insurance, financial services, healthcare, and retail/consumer package goods industries trust Coginiti’s collaborative data workspace to deliver value to their customers.

Cayley is an open-source database for Linked Data. It is inspired by the graph database behind Google's Knowledge Graph (formerly Freebase). Cayley is an open-source graph database designed for ease of use and storing complex data. Built-in query editor, visualizer and REPL. Cayley can use multiple query languages like Gizmo, a query language inspired by Gremlin, GraphQL-inspired query language, MQL a simplified version for Freebase fans. Cayley is modular, easy to connect to your favorite programming languages and back-end stores, production ready, well tested and used by various companies for their production workloads and fast with optimized specifically for usage in applications. Rough performance testing shows that, on 2014 consumer hardware and an average disk, 134m quads in LevelDB is no problem and a multi-hop intersection query- films starring X and Y - takes ~150ms. Cayley is configured by default to run in memory (That's what backend memstore means).

Claravine is redefining data integrity for the global enterprise. The Data Standards Cloud makes it easy for teams to standardize, connect, and control data collaboratively, across the organization. Leading brands use Claravine to take greater ownership and control of their data from the start, for better decisions, stickier consumer experiences, and increased ROI.

HALCYON is a data collaboration platform that ensures the right data is delivered at the right time. It provides all stakeholders with a hub to supply, validate and approve engineering data then creates an immutable record of that data. HALCYON automates the capture of granular engineering data and improves collaboration across the supply chain. The activities that HALCYON captures, happen now, just in many disparate forms and sources, we bring all of this together into a rich, central data environment that connects the teams and their data. HALCYON is the world’s only blockchain information management platform and creates a permanent digital golden thread of the information, decisions and queries made during projects. Simple to configure and then simple to load, share and action on information from your data supply chain. Everyone has visibility on what they need to do and by when making it simple to action and comply.

Create new streams of revenue using the data you already collect with your own branded data shop. Narrative is focused on the fundamental principles that make buying and selling data easier, safer, and more strategic. Ensure that the data you access meets your standards, whatever they may be. Know exactly who you’re working with and how the data was collected. Easily access new supply and demand for a more agile and accessible data strategy. Own your data strategy entirely with end-to-end control of inputs and outputs. Our platform simplifies and automates the most time- and labor-intensive aspects of data acquisition, so you can access new data sources in days, not months. With filters, budget controls, and automatic deduplication, you’ll only ever pay for the data you need, and nothing that you don’t.

Hex brings together the best of notebooks, BI, and docs into a seamless, collaborative UI. Hex is a modern Data Workspace. It makes it easy to connect to data, analyze it in collaborative SQL and Python-powered notebooks, and share work as interactive data apps and stories. Your default landing page in Hex is the Projects page. You can quickly find projects you created, as well as those shared with you and your workspace. The outline provides an easy-to-browse overview of all the cells in a project's Logic View. Every cell in the outline lists the variables it defines, and cells that return a displayed output (chart cells, Input Parameters, markdown cells, etc.) display a preview of that output. You can click any cell in the outline to automatically jump to that position in the logic.

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.

Einblick is the fastest and most collaborative way to explore data, create predictions, and deploy data apps. Our canvases radically change data science workflows by making it so much easier to explore, clean, and manipulate data on a novel interface. We are the only platform that let you collaborate in real-time with your whole team. Decision-making is a group activity, so let’s get everyone involved. Don’t waste time hand-tuning models. Our AutoML is focused on helping you create explainable predictions and identify key drivers without fuss. Einblick packages common analytics functionality into easy-to-use operators that let you abstract repetitive tasks and get to answers faster. From Snowflake to S3 buckets to CSV files, connect your data source and start getting to answers within minutes. Take a list of churned and current customers and join in everything you know about them. Uncover the key factors that led to churn, and identify how at-risk every customer is.

Build and orchestrate ETL pipelines with ease on Boltic. Extract, transform, and load data from multiple sources to any destination without writing code. Use advanced transformations and build end-to-end data pipelines for analytics-ready data. Integrate data from a list of 100+ pre-built Integrations and join multiple data sources together with a few clicks to work on the cloud. Add Boltic’s No-code transformation or use Script Engine to design custom scripts on integrated data for data exploration and cleansing. Invite team members to come together and solve organisation-wide problems faster by working on a secure cloud data operations platform. Schedule ETL pipelines to run automatically at pre-defined time intervals to make importing, cleaning, transforming, storing, and sharing data easier. Track and analyze key metrics of business with the help of AI & ML. Gain insights into business and monitor for potential issues or opportunities.

Realtime, decentralized, offline-first, graph database engine. The data that needs to stored, loaded, and shared in your app without worrying about servers, network calls, databases, or tracking offline changes or concurrency conflicts. GUN is a small, easy, and fast data sync and storage system that runs everywhere JavaScript does. The aim of GUN is to let you focus on the data that needs to be stored, loaded, and shared in your app without worrying about servers, network calls, databases, or tracking offline changes or concurrency conflicts. This lets you build cool apps fast. GUN gives you the most powerful weapons of the internet — decentralization and real privacy — to reclaim the web and make it truly free and open. GUN is a data­base en­gine that runs every­where JavaScript does — browsers, mo­bile de­vices and servers, al­low­ing you to build ex­act­ly the data sys­tem you want.

data.world is a fully managed service, born in the cloud, and optimized for modern data architectures. That means we handle all updates, migrations, and maintenance. Set up is fast and simple with a large and growing ecosystem of pre-built integrations including all of the major cloud data warehouses. When time-to-value is critical, your team needs to solve real business problems, not fight with hard-to-manage data software. data.world makes it easy for everyone, not just the "data people", to get clear, accurate, fast answers to any business question. Our cloud-native data catalog maps your siloed, distributed data to familiar and consistent business concepts, creating a unified body of knowledge anyone can find, understand, and use. In addition to our enterprise product, data.world is home to the world’s largest collaborative open data community. It’s where people team up on everything from social bot detection to award-winning data journalism.

End-to-end data clean room platform, integrated for activation. Publishers and advertisers use Optable data clean room technology to securely plan, activate and measure advertising campaigns. A new generation of privacy-preserving data collaboration software. Optable customers can collaborate with their customers and partners, including those who aren't Optable customers themselves. This can be done using the platform's Flash Nodes, allowing to invite other parties into a secure environment. Optable offers a decentralized identity infrastructure, allowing to build of private identity graphs. The infrastructure provides means for creating purpose-limited, permission data clean rooms that minimize data movement. Interoperability with data warehouses and other data clean rooms is key. The use of our open-source software allows third-party platforms to match data with Optable customers, as well as implement secure clean room functions for their own use.

MLReef enables domain experts and data scientists to securely collaborate via a hybrid of pro-code & no-code development approaches. 75% increase in productivity due to distributed workloads. This enables teams to complete more ML projects faster. Domain experts and data scientists collaborate on the same platform reducing 100% of unnecessary communication ping-pong. MLReef works on your premises and uniquely enables 100% reproducibility and continuity. Rebuild all work at any time. You can use already well-known and established git repositories to create explorable, interoperable, and versioned AI modules. AI Modules created by your data scientists become drag-and-drop elements. These are adjustable by parameters, versioned, interoperable, and explorable within your entire organization. Data handling often requires expert knowledge that a single data scientist often lacks. MLReef enables your field experts to relieve your data processing task, reducing complexities.

Understand how users are interacting with your product and identify opportunity areas to inform your product decisions. Mode empowers one Stitch analyst to do the work of a full data team through speed, flexibility, and collaboration. Build dashboards for annual revenue, then use chart visualizations to identify anomalies quickly. Create polished, investor-ready reports or share analysis with teams for collaboration. Connect your entire tech stack to Mode and identify upstream issues to improve performance. Speed up workflows across teams with APIs and webhooks. Understand how users are interacting with your product and identify opportunity areas to inform your product decisions. Leverage marketing and product data to fix weak spots in your funnel, improve landing-page performance, and understand churn before it happens.

Bitfount is a platform for distributed data science. We power deep data collaborations without data sharing. Distributed data science sends algorithms to data, instead of the other way around. Set up a federated privacy-preserving analytics and machine learning network in minutes, and let your team focus on insights and innovation instead of bureaucracy. Your data team has the skills to solve your biggest challenges and innovate, but they are held back by barriers to data access. Is complex data pipeline infrastructure messing with your plans? Are compliance processes taking too long? Bitfount has a better way to unleash your data experts. Connect siloed and multi-cloud datasets while preserving privacy and respecting commercial sensitivity. No expensive, time-consuming data lift-and-shift. Usage-based access controls to ensure teams only perform the analysis you want, on the data you want. Transfer management of access controls to the teams who control the data.

PuppyGraph empowers you to seamlessly query one or multiple data stores as a unified graph model. Graph databases are expensive, take months to set up, and need a dedicated team. Traditional graph databases can take hours to run multi-hop queries and struggle beyond 100GB of data. A separate graph database complicates your architecture with brittle ETLs and inflates your total cost of ownership (TCO). Connect to any data source anywhere. Cross-cloud and cross-region graph analytics. No complex ETLs or data replication is required. PuppyGraph enables you to query your data as a graph by directly connecting to your data warehouses and lakes. This eliminates the need to build and maintain time-consuming ETL pipelines needed with a traditional graph database setup. No more waiting for data and failed ETL processes. PuppyGraph eradicates graph scalability issues by separating computation and storage.

GraphBase is a Graph Database Management System (Graph DBMS) engineered to simplify the creation and maintenance of complex data graphs. Complex and highly-connected structures are a challenge for the Relational Database Management System (RDBMS). A graph database provides much better modelling utility, performance and scalability. The current crop of graph database products - the triplestores and property graphs - have been around for nearly two decades. They're powerful tools, they have many uses, but they're still not suited to the management of complex data structures. With GraphBase, our goal was to simplify the management of complex data structures, so that your data could become something more. It could become Knowledge. We achieved this by redefining how graph data should be managed. In GraphBase, the graph is a first-class citizen. You get a graph equivalent of the "rows and tables" paradigm that makes a Relational Database so easy to use.

Amazon Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency. Amazon Neptune supports popular graph models Property Graph and W3C's RDF, and their respective query languages Apache TinkerPop Gremlin and SPARQL, allowing you to easily build queries that efficiently navigate highly connected datasets. Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security. Proactively detect and investigate IT infrastructure using a layered security approach. Visualize all infrastructure to plan, predict and mitigate risk. Build graph queries for near-real-time identity fraud pattern detection in financial and purchase transactions.

Morph's AI helps you to collect, sort, and analyze your data. Just tell it what you need in plain language. No more sending files back and forth, work together in your dataset in real-time. Robust API support lets you access Morph's features unfiltered. Don't let the friendly face fool you; it's running Postgres under the hood. As easy to use as a spreadsheet, but designed to handle millions of records. Manage access between different users and teams with a single click. Regardless of the format your data is in, upload it with everything in the right place. We believe that data should be easy for everyone to collect, store, and understand, in one simple interface. Makes easy and powerful use of data available to not just engineers but also marketing, sales, customer support, and management. We have been building business software and end-user software for various companies for seven years. This included projects that dealt with complex data, such as machine learning and blockchain.

HugeGraph is a fast-speed and highly-scalable graph database. Billions of vertices and edges can be easily stored into and queried from HugeGraph due to its excellent OLTP ability. As compliance to Apache TinkerPop 3 framework, various complicated graph queries can be accomplished through Gremlin (a powerful graph traversal language). Among its features, it provides compliance to Apache TinkerPop 3, supporting Gremlin. Schema Metadata Management, including VertexLabel, EdgeLabel, PropertyKey and IndexLabel. Multi-type Indexes, supporting exact query, range query and complex conditions combination query. Plug-in Backend Store Driver Framework, supporting RocksDB, Cassandra, ScyllaDB, HBase and MySQL now and easy to add other backend store driver if needed. Integration with Hadoop/Spark. HugeGraph relies on the TinkerPop framework, we refer to the storage structure of Titan and the schema definition of DataStax.

Luna is a subscription to the Apache Cassandra support and expertise at DataStax. It allows you to enjoy all the benefits of open-source Cassandra, with the peace of mind knowing you have direct access to the team that authored the majority of the code and supported some of the largest deployments in the world. Best practices, advice, and SLA-based support to keep your Cassandra deployment in top shape. Scale without compromising on performance or latency to seamlessly manage the most demanding real-time workloads. Create real-time and highly-interactive customer experiences with blisteringly fast read and writes. Luna provides assistance with resolving issues and following best practices with Cassandra clusters. Services provide help through the full application life cycle, with a deeper integration in your team working together on implementation.

QEDIT is an enterprise-ready, cross-organizational data collaboration platform engineered for the new data economy. We leverage the latest innovations in privacy-enhancing technology to help you safely monetize data assets, improve business analytics processes and gain actionable insights from 2nd parties in a risk-free environment. Our highly scalable, cloud-hosted platform seamlessly integrates with legacy database systems so you can be up and running in no time. QEDIT provides you with timely, business-critical intelligence through a configurable dashboard, advanced reporting functionality, real-time notifications and more. QEDIT empowers companies to engage in regulatory-compliant data collaboration to accelerate growth, mitigate risk and solve complex business problems. QEDIT is an enterprise-ready, secure data collaboration platform that enables companies to share intelligence and monetize data insights derived from external sources, without revealing confidential information.

Nextflow Tower is an intuitive centralized command post that enables large-scale collaborative data analysis. With Tower, users can easily launch, manage, and monitor scalable Nextflow data analysis pipelines and compute environments on-premises or on most clouds. Researchers can focus on the science that matters rather than worrying about infrastructure engineering. Compliance is simplified with predictable, auditable pipeline execution and the ability to reliably reproduce results obtained with specific data sets and pipeline versions on demand. Nextflow Tower is developed and supported by Seqera Labs, the creators and maintainers of the open-source Nextflow project. This means that users get high-quality support directly from the source. Unlike third-party frameworks that incorporate Nextflow, Tower is deeply integrated and can help users benefit from Nextflow's complete set of capabilities.

Get consumer insights without sharing or exposing Personal Data. Karlsgate Identity Exchange (KIE™) matches data anonymously on-the-fly using patent-pending Cryptoidentity technology. Market data while achieving consumer privacy compliance that goes beyond current regulations. KIE gives data providers maximum control and data transparency. Reduce data acquisition from months to minutes. KIE streamlines evaluation, contracting and data management tasks to get you up and running quickly. Simplify data processing with sophisticated input file-matching logic. KIE delivers high-confidence file matching using deterministic cascading match algorithms. With Karlsgate, companies can build strategic data collaboration partnerships without sharing the PII of their customers. In addition, the data appending process is immediate and ensures both recency and accuracy of attributes, so you never have to worry that your enhanced data set is out-of-date.

ZinkML is a zero-code data science platform designed to address the challenges faced by organizations in leveraging data effectively. By providing a visual and intuitive interface, it eliminates the need for extensive coding expertise, making data science accessible to a broader range of users. ZinkML streamlines the entire data science lifecycle, from data ingestion and preparation to model building, deployment, and monitoring. Users can drag-and-drop components to create complex data pipelines, explore data visually, and build predictive models without writing a single line of code. The platform also offers automated feature engineering, model selection, and hyperparameter tuning, accelerating the model development process. Moreover, ZinkML provides robust collaboration features, enabling teams to work together seamlessly on data science projects. By democratizing data science, we empower companies to extract maximum value from their data and drive better decision-making.

OpenText™ Lens™ is a powerful, user-friendly cloud application that offers visibility into the data flows between enterprise applications and connected systems, customers, suppliers, and trading partners. With Lens, organizations gain insights needed to monitor business process health against KPIs, quickly respond to key business events and improve overall productivity. Make insights into integrated data flows easily accessible for business users to extend visibility beyond the IT team. Get a best-in-class user experience, personalized through notifications, alerts, reporting, and collaboration. See everything in one place with a single view into all data flows processed on the OpenText™ Trading Grid™ platform. Leverage full visibility across different types of integration flows for detailed insights into business processes in near real-time. Use data-driven insights to agilely manage and respond to unforeseen issues and mitigate risks before they impact business.

InfoLobby is an online business data management and team collaboration platform. Build tables for data with simple drag & drop and spread those tables over workspaces so that users can have access to only those tables they should. Assign tasks to users and manage your delegated tasks easily. Email is built-in so you can communicate with external contacts on your individual records. The built-in automation engine is super powerful and fast. You can leverage the automation engine to modify your data, send emails, create PDF's, interact with any oAuth2 API, and much more. The application works flawlessly in modern web browsers on any sized device, from your phone to your desktop. Unlike similar platforms, pricing is tiered by user role, so you don't have to pay a fortune for all those regular users who only input occasional data.

Graph databases, part of Oracle’s converged database offering, eliminate the need to set up a separate database and move data. Analysts and developers can perform fraud detection in banking, find connections and link to data, and improve traceability in smart manufacturing, all while gaining enterprise-grade security, ease of data ingestion, and strong support for data workloads. Oracle Autonomous Database includes Graph Studio, with one-click provisioning, integrated tooling, and security. Graph Studio automates graph data management and simplifies modeling, analysis, and visualization across the graph analytics lifecycle. Oracle provides support for both property and RDF knowledge graphs, and simplifies the process of modeling relational data as graph structures. Interactive graph queries can run directly on graph data or in a high-performance in-memory graph server.

With a huge collection of analytical features, AnzoGraph DB can enhance your analytical framework. Watch this video to learn how AnzoGraph DB is a Massively Parallel Processing (MPP) native graph database that is built for data harmonization and analytics. Horizontally scalable graph database built for online analytics and data harmonization. Take on data harmonization and linked data challenges with AnzoGraph DB, a market-leading analytical graph database. AnzoGraph DB provides industrialized online performance for enterprise-scale graph applications. AnzoGraph DB uses familiar SPARQL*/OWL for semantic graphs but also supports Labeled Property Graphs (LPGs). Access to many analytical, machine learning and data science capabilities help you achieve new insights, delivered at unparalleled speed and scale. Use context and relationships between data as first-class citizens in your analysis. Ultra-fast data loading and analytical queries.

Titan is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. Titan is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time. Elastic and linear scalability for a growing data and user base. Data distribution and replication for performance and fault tolerance. Multi-datacenter high availability and hot backups. Support for ACID and eventual consistency. Support for various storage backends like Apache Cassandra, Apache HBase and Oracle BerkeleyDB. Support for global graph data analytics, reporting, and ETL through integration with big data platforms like Apache Spark, Apache Giraph and Apache Hadoop. Native integration with the TinkerPop graph stack for Gremlin graph query language, Gremlin graph server and Gremlin applications.

CorralData is a full-service, AI-powered platform that radically simplifies unifying and analyzing data across multiple sources. With CorralData, you can access human data experts and industry-leading AI tools to easily and cost-effectively drive remarkable, data-fueled results. No coding, SQL, or engineering resources required. Here’s how CorralData works. First, unify all of your data sources using our 450+ pre-built data connectors. Our U.S.-based support team will guide you along the way. Then, begin instantly and securely unlocking powerful data insights using natural language AI questions. Or work directly with a human data expert to surface the insight you need. The CorralData platform includes everything you need to start using data to drive results in one simple, monthly subscription—stunning data visualization tools, built-in chat, custom reporting, and access to human experts. Schedule a free demo today and see how simple and easy AI-powered data can be.

JanusGraph is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. JanusGraph is a project under The Linux Foundation, and includes participants from Expero, Google, GRAKN.AI, Hortonworks, IBM and Amazon. Elastic and linear scalability for a growing data and user base. Data distribution and replication for performance and fault tolerance. Multi-datacenter high availability and hot backups. All functionality is totally free. No need to buy commercial licenses. JanusGraph is fully open source under the Apache 2 license. JanusGraph is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time. Support for ACID and eventual consistency. In addition to online transactional processing (OLTP), JanusGraph supports global graph analytics (OLAP) with its Apache Spark integration.

RecallGraph is a versioned-graph data store - it retains all changes that its data (vertices and edges) have gone through to reach their current state. It supports point-in-time graph traversals, letting the user query any past state of the graph just as easily as the present. RecallGraph is a potential fit for scenarios where data is best represented as a network of vertices and edges (i.e., a graph) having the following characteristics: 1. Both vertices and edges can hold properties in the form of attribute/value pairs (equivalent to JSON objects). 2. Documents (vertices/edges) mutate within their lifespan (both in their individual attributes/values and in their relations with each other). 3. Past states of documents are as important as their present, necessitating retention and queryability of their change history. Also see this blog post for an intro - https://blog.recallgraph.tech/never-lose-your-old-data-again.

Through its Native Parallel Graph™ technology, the TigerGraph™ graph platform represents what’s next in the graph database evolution: a complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time. Combining the best ideas (MapReduce, Massively Parallel Processing, and fast data compression/decompression) with fresh development, TigerGraph delivers what you’ve been waiting for: the speed, scalability, and deep exploration/querying capability to extract more business value from your data.

Fluree is an immutable RDF graph database written in Clojure and adhering to W3C standards, supporting JSON and JSON-LD while accommodating various RDF ontologies; it boasts a scalable, cloud-native architecture utilizing a lightweight Java runtime, with individually scalable ledger and graph database components, embodying a "Data-Centric" ideology that treats data as a reusable asset independent of singular applications, underpinned by an immutable ledger that secures transactions with cryptographic integrity, alongside a rich RDF graph database capable of various queries, and employs SmartFunctions for enforcing data management rules, including identity and access management and data quality.

Confidently branch, review, and merge data as you experiment with complete history and recoverability. Track your code and data together for always-in-sync development and guaranteed reproducibility. Automate reports, audit access, and manage metadata in a centralized location for everyone. XetHub is ideal for teams who already use Git to track their code changes, and want to leverage the power of infinite history, pull requests, and difference-based tracking for larger assets such as datasets or media files. Managing complete projects with familiar Git semantics makes change tracking and continuous integration a breeze, especially for workflows that use code to generate or augment assets.

Graphlytic is a customizable web platform for knowledge graph visualization and analysis. Users can interactively explore the graph, look for patterns with the Cypher or Gremlin query languages (or query templates for non-tech users), or use filters to find the answers to any graph question. The graph visualization brings deep insights in industries, such as scientific research, anti-fraud investigation, etc. Users with very little graph theory knowledge can start to explore the data in no time. Graph rendering is done with the Cytoscape.js library which allows us to render tens of thousands of nodes and hundreds of thousands of relationships. The application is provided in three ways: Desktop, Cloud, and Server. Graphlytic Desktop is a free Neo4j Desktop application installed in just a few clicks. Cloud instances are ideal for small teams that don't want to worry about the installation and need to get up and running in very little time.

VelocityDB is a database engine like no other. It can store data faster and more efficiently than any other solution at a fraction of the cost of other database engines. It stores .NET objects as they are with no mapping to tables, JSON or XML. VelocityGraph is an add on open source property graph database that can be used in conjunction with the VelocityDB object database. Object and graph database engine VelocityDB is a C# .NET noSQL object fatabase, extended as graph database is VelocityGraph. World’s fastest most scalable & flexible database. A bug reported with a reproducible test case is usually fixed within a week. The most important benefit is the flexibility that this database system provides. No other types of database system lets you fine tune your application to the finest details. Using VelocityDB, you can choose the best possible data structures for your application. You can control where you place the data persistently and how it's indexed and accessed.

Natively store data for graph, document and search needs. Utilize feature-rich access with one query language. Map data natively to the database and access it with the best patterns for the job – traversals, joins, search, ranking, geospatial, aggregations – you name it. Polyglot persistence without the costs. Easily design, scale and adapt your architectures to changing needs and with much less effort. Combine the flexibility of JSON with semantic search and graph technology for next generation feature extraction even for large datasets.

Building intelligent systems starts at the database. Grakn is an intelligent database - a knowledge graph. An insanely intuitive & expressive data schema, with constructs to define hierarchies, hyper-entities, hyper-relations and rules, to build rich knowledge models. An intelligent language that performs logical inference of data types, relationships, attributes and complex patterns, during runtime, and over distributed & persisted data. Out-of-the-box distributed analytics (Pregel and MapReduce) algorithms, accessible through the language through simple queries. Strong abstraction over low-level patterns, enabling simpler expressions of complex constructs, while the system figures out the most optimal query execution. Scale your enterprise Knowledge Graph with Grakn KGMS and Workbase. A distributed database designed to scale over a network of computers through partitioning and replication.

RelationalAI is a next-generation database system for intelligent data applications based on relational knowledge graphs. Data-centric application design brings data and logic together into composable models. Intelligent data applications understand and make use of each relation that exists in a model. relational provides a knowledge graph system to express knowledge as executable models. These models can be easily extended through declarative, human-readable programs. RelationalAI’s expressive, declarative language leads to a 10-100x reduction in code. Applications are developed faster, with superior quality by bringing non-technical domain experts into the creation process and by automating away complex programming tasks. Take advantage of the extensible graph data model as the foundation of data-centric architecture. Integrate models to discover new relationships and break down barriers between applications.

The Open, Multi-Cloud Stack for Modern Data Apps. Built on open-source Apache Cassandra™. Global-scale and 100% uptime without vendor lock-in. Deploy on multi-cloud, on-prem, open-source, and Kubernetes. Elastic and pay-as-you-go for improved TCO. Start building faster with Stargate APIs for NoSQL, real-time, reactive, JSON, REST, and GraphQL. Skip the complexity of multiple OSS projects and APIs that don’t scale. Ideal for commerce, mobile, AI/ML, IoT, microservices, social, gaming, and richly interactive applications that must scale-up and scale-down with demand. Get building modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Use REST, GraphQL, JSON with your favorite full-stack framework Richly interactive apps that are elastic and viral-ready from Day 1. Pay-as-you-go Apache Cassandra DBaaS that scales effortlessly and affordably.

Manage complex models using ArcadeDB without any compromise. Forget about Polyglot Persistence. no need for multiple databases. You can store graphs, documents, key values and time series all in one ArcadeDB Multi-Model database. Since each model is native to the database engine, you don't have to worry about translations slowing you down. ArcadeDB's engine was built with Alien Technology. It's able to crunch millions of records per second. With ArcadeDB, the traversing speed is not affected by the database size. It is always constant, whether your database has a few records or billions. ArcadeDB can work as an embedded database, on a single server and can scale up using multiple servers with Kubernetes. Flexible enough to run on any platform with a small footprint. Your data is secure. Our unbreakable fully transactional engine assures durability for mission-critical production databases. ArcadeDB uses a Raft Consensus Algorithm to maintain consistency across multiple servers.

The Datastreams Platform is our state-of-the-art solution to simplify the process of capturing, sharing and managing data within and between organizations. From the initial step of collecting the right data towards getting a trusted personalized data view, our Platform facilitates the journey. Fast through optimized streaming technology, simple due to its patented data capturing capabilities and secured per our privacy by design principles, data collaboration is now available for everyone! The Platform is built upon a core Data Operations Unit (Datastreams Operator) that can be extended with different modules to fulfill specific data and business requirements like data quality checks on your web/mobile platforms or defining and segmenting specific target groups in a compliant way. Designed with IT & business agility in mind, it takes just a couple of days to start data collaborating with connections to data sources.

Automatically indexed warehouses, lakes, dashboards, and other pieces of your data stack. Combined with utilization, lineage, and other social popularity signals, Metaphor lets you show the most trusted data to your users. Provide an open 360 view of your data and conversations about data to everyone in the organization. Meet your customers where they are - share artifacts from the catalog including documentation, natively via Slack. Tag insightful Slack conversations and associate them with data. Collaborate across silos by the organic discovery of important terms and usage patterns. Easily discover data across the entire stack, write technical details and Business friendly wiki that is easily consumed by non-technical users. Support your users directly in Slack and use the catalog as a Data Enablement tool to quickly onboard users for a more personalized experience.