JanusGraph is a highly scalable graph database optimized for storing and querying large graphs with billions of vertices and edges distributed across a multi-machine cluster. JanusGraph is a transactional database that can support thousands of concurrent users, complex traversals, and analytic graph queries.

In addition, JanusGraph provides the following features:

  • 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:

  • Apache Cassandra®
  • Apache HBase®
  • Google Cloud Bigtable
  • Oracle BerkeleyDB

Support for global graph data analytics, reporting, and ETL through integration with big data platforms:

  • Apache Spark™
  • Apache Giraph™
  • Apache Hadoop®

Support for geo, numeric range, and full-text search via:

  • ElasticSearch™
  • Apache Solr™
  • Apache Lucene®

Native integration with the Apache TinkerPop™ graph stack:

  • Gremlin graph query language
  • Gremlin graph server
  • Gremlin applications
  • Open source under the Apache 2 license

You can visualize graphs stored in JanusGraph via any of the following tools:

  • Cytoscape
  • Gephi plugin for Apache TinkerPop
  • Graphexp
  • KeyLines by Cambridge Intelligence
  • Linkurious
  • The Benefits of JanusGraph

JanusGraph is designed to support the processing of graphs so large that they require storage and computational capacities beyond what a single machine can provide. Scaling graph data processing for real time traversals and analytical queries is JanusGraph’s foundational benefit. This section will discuss the various specific benefits of JanusGraph and its underlying, supported persistence solutions.

General JanusGraph Benefits

  • Support for very large graphs. JanusGraph graphs scale with the number of machines in the cluster.
  • Support for very many concurrent transactions and operational graph processing. JanusGraph’s transactional capacity scales with the number of machines in the cluster and answers complex traversal queries on huge graphs in milliseconds.
  • Support for global graph analytics and batch graph processing through the Hadoop framework.
  • Support for geo, numeric range, and full-text search for vertices and edges on very large graphs.
  • Native support for the popular property graph data model exposed by Apache TinkerPop.
  • Native support for the graph traversal language Gremlin.
  • Easy integration with the Gremlin Server for programming language agnostic connectivity.
  • Numerous graph-level configurations provide knobs for tuning performance.
  • Vertex-centric indices provide vertex-level querying to alleviate issues with the infamous supernode problem.
  • Provides an optimized disk representation to allow for efficient use of storage and speed of access.
  • Open source under the liberal Apache 2 license.

Benefits of JanusGraph with Apache Cassandra

  • cassandra-small
  • Continuously available with no single point of failure.
  • No read/write bottlenecks to the graph as there is no master/slave architecture.
  • Elastic scalability allows for the introduction and removal of machines.
  • Caching layer ensures that continuously accessed data is available in memory.
  • Increase the size of the cache by adding more machines to the cluster.
  • Integration with Apache Hadoop.
  • Open source under the liberal Apache 2 license.

Benefits of JanusGraph with HBase

  • hbase_logo
  • Tight integration with the Apache Hadoop ecosystem.
  • Native support for strong consistency.
  • Linear scalability with the addition of more machines.
  • Strictly consistent reads and writes.
  • Convenient base classes for backing Hadoop MapReduce jobs with HBase tables.
  • Support for exporting metrics via JMX.
  • Open source under the liberal Apache 2 license

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