Struggling to choose between JanusGraph and Orient DB? Both products offer unique advantages, making it a tough decision.
JanusGraph is a Development solution with tags like graph, database, distributed, scalable, cassandra, hbase.
It boasts features such as Distributed graph database, Supports various storage backends like Cassandra, HBase, etc, Scalable to handle large graphs, Support for complex traversals and graph algorithms, Native integration with Spark and TinkerPop Gremlin, Support for geo, numeric range and full-text search, ACID and serializable transactions, Multi-datacenter high availability and pros including Highly scalable, Flexible storage backend options, Strong consistency support, Powerful graph querying capabilities, Integrates well with big data stack.
On the other hand, Orient DB is a Development product tagged with nosql, document-database, graph-database, schemaless, open-source.
Its standout features include Graph database model, Document database model, Distributed architecture, SQL support, ACID transactions, Query language (OrientQL), Native integration with Java, .NET, Node.js, and it shines with pros like Powerful querying through relationships, Flexible schema-less data model, High performance, Strong data consistency, Open source with commercial support available.
To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.
JanusGraph is a scalable, distributed graph database optimized for storing and querying large graphs. It is an open source project under the Linux Foundation and supports storage backends like Cassandra and HBase.
OrientDB is an open source NoSQL database management system that combines the flexibility of document databases with the power of graph databases. It uses a document graph data model to store data in a schema-less format, allowing for efficient querying and indexing of relationships.