Best Data Management Software for JanusGraph
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Compare the Top Data Management Software that integrates with JanusGraph as of June 2025
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This a list of Data Management software that integrates with JanusGraph. Use the filters on the left to add additional filters for products that have integrations with JanusGraph. View the products that work with JanusGraph in the table below.
What is Data Management Software for JanusGraph?
Data management software systems are software platforms that help organize, store and analyze information. They provide a secure platform for data sharing and analysis with features such as reporting, automation, visualizations, and collaboration. Data management software can be customized to fit the needs of any organization by providing numerous user options to easily access or modify data. These systems enable organizations to keep track of their data more efficiently while reducing the risk of data loss or breaches for improved business security. Compare and read user reviews of the best Data Management software for JanusGraph currently available using the table below. This list is updated regularly.
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1
Elasticsearch
Elastic
Elastic is a search company. As the creators of the Elastic Stack (Elasticsearch, Kibana, Beats, and Logstash), Elastic builds self-managed and SaaS offerings that make data usable in real time and at scale for search, logging, security, and analytics use cases. Elastic's global community has more than 100,000 members across 45 countries. Since its initial release, Elastic's products have achieved more than 400 million cumulative downloads. Today thousands of organizations, including Cisco, eBay, Dell, Goldman Sachs, Groupon, HP, Microsoft, Netflix, The New York Times, Uber, Verizon, Yelp, and Wikipedia, use the Elastic Stack, and Elastic Cloud to power mission-critical systems that drive new revenue opportunities and massive cost savings. Elastic has headquarters in Amsterdam, The Netherlands, and Mountain View, California; and has over 1,000 employees in more than 35 countries around the world. -
2
Apache Cassandra
Apache Software Foundation
The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance. Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. Cassandra's support for replicating across multiple datacenters is best-in-class, providing lower latency for your users and the peace of mind of knowing that you can survive regional outages. -
3
Hackolade
Hackolade
Hackolade Studio is a powerful data modeling platform that supports a wide range of technologies including relational SQL and NoSQL databases, cloud data warehouses, APIs, streaming platforms, and data exchange formats. Designed for modern data architecture, it enables users to visually design, document, and evolve schemas across systems like Oracle, PostgreSQL, Databricks, Snowflake, MongoDB, Cassandra, DynamoDB, Neo4j, Kafka (with Confluent Schema Registry), OpenAPI, GraphQL, and more. Hackolade Studio offers forward and reverse engineering, schema versioning, model validation, and integration with metadata catalogs such as Unity Catalog and Collibra. It empowers data architects, engineers, and governance teams to collaborate on consistent, governed, and scalable data models. Whether building data products, managing API contracts, or ensuring regulatory compliance, Hackolade Studio streamlines the process in one unified interface.Starting Price: €175 per month -
4
Graphlytic
Demtec
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.Starting Price: 19 EUR/month -
5
KgBase
KgBase
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.Starting Price: $19 per month -
6
Oracle Berkeley DB
Oracle
Berkeley DB is a family of embedded key-value database libraries providing scalable high-performance data management services to applications. The Berkeley DB products use simple function-call APIs for data access and management. Berkeley DB enables the development of custom data management solutions, without the overhead traditionally associated with such custom projects. Berkeley DB provides a collection of well-proven building-block technologies that can be configured to address any application need from the hand-held device to the data center, from a local storage solution to a world-wide distributed one, from kilobytes to petabytes. -
7
KeyLines
Cambridge Intelligence
Build game-changing graph visualization products that turn connected data into insight. Harness JavaScript’s power and flexibility to quickly and easily build graph visualization applications that can be deployed anywhere, to anyone. KeyLines is a completely flexible way to build your graph visualization application. Build interactive graph visualization tools to reveal threats and hidden insight. The KeyLines JavaScript graph visualization toolkit lets you build applications specifically for your users, your data, and the questions you need to answer. It fits with any browser, device, server, or database and comes with clear tutorials, demos, and API documentation. Combined with our developer support, you’ll be uncovering network insight in no time. KeyLines makes it easy to build high-performance JavaScript graph visualization tools that work anywhere. They harness HTML5 and WebGL graphics rendering and thoughtfully crafted code to give users fast and insightful visualization. -
8
ReGraph
Cambridge Intelligence
Build game-changing React graph visualization products that turn connected data into insight. With ReGraph’s simple data-driven API, it’s quick and easy to add graph visualizations to your React applications. Ship custom, high-performance graph visualization to your users, wherever they are. For React developers, ReGraph offers a simple and clean coding experience. It has familiar logic, easy state handling, and well-documented props. You can choose where your data is stored, and how the component looks and behaves. It works in any browser, on any device, and integrates readily with any server or database. It’s a completely flexible way to build a custom React graph visualization application. ReGraph makes it easy to build powerful React graph visualization applications. Everything has been carefully optimized for performance, from its layout algorithms to its supercharged graphics rendering engine. -
9
Apache HBase
The Apache Software Foundation
Use Apache HBase™ when you need random, realtime read/write access to your Big Data. This project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware. Automatic failover support between RegionServers. Easy to use Java API for client access. Thrift gateway and a REST-ful Web service that supports XML, Protobuf, and binary data encoding options. Support for exporting metrics via the Hadoop metrics subsystem to files or Ganglia; or via JMX. -
10
Apache Spark
Apache Software Foundation
Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources. -
11
Google Cloud Bigtable
Google
Google Cloud Bigtable is a fully managed, scalable NoSQL database service for large analytical and operational workloads. Fast and performant: Use Cloud Bigtable as the storage engine that grows with you from your first gigabyte to petabyte-scale for low-latency applications as well as high-throughput data processing and analytics. Seamless scaling and replication: Start with a single node per cluster, and seamlessly scale to hundreds of nodes dynamically supporting peak demand. Replication also adds high availability and workload isolation for live serving apps. Simple and integrated: Fully managed service that integrates easily with big data tools like Hadoop, Dataflow, and Dataproc. Plus, support for the open source HBase API standard makes it easy for development teams to get started. -
12
Apache Atlas
Apache Software Foundation
Atlas is a scalable and extensible set of core foundational governance services – enabling enterprises to effectively and efficiently meet their compliance requirements within Hadoop and allows integration with the whole enterprise data ecosystem. Apache Atlas provides open metadata management and governance capabilities for organizations to build a catalog of their data assets, classify and govern these assets and provide collaboration capabilities around these data assets for data scientists, analysts and the data governance team. Pre-defined types for various Hadoop and non-Hadoop metadata. Ability to define new types for the metadata to be managed. Types can have primitive attributes, complex attributes, object references; can inherit from other types. Instances of types, called entities, capture metadata object details and their relationships. REST APIs to work with types and instances allow easier integration. -
13
InformationGrid
InformationGrid
Most businesses are aware that data can help them to understand their customers better to improve processes and solve problems. We have developed a safe solution for sharing and aggregating data: InformationGrid. Get valuable insights with InformationGrid, a safe solution for sharing and aggregating data. A solution that allows hospitals and general practitioners to share data in order to prescribe better medications. Whether you have a clear idea of your data strategy or need some guidance defining this; we’re here to help you put your data strategy into action. Our SAAS platform enables you to share and aggregate data in a way that’s secure and cost-efficient. To keep time to value as short as possible we can build an application that can handle large amounts of data, and we can build it fast by using cloud-native techniques. This enables you to reap the short-term benefits of the data and get ready to start using AI to advance your business.
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