Neo Technology, creator of Neo4j, the world’s leading graph database, today announced the immediate availability of Neo4j 2.2, with major updates allowing organizations to derive maximum value from their data relationships. Enhancements in Neo4j 2.2 include significantly improved read and write performance, which organizations can put to immediate use to build even faster, more powerful mission-critical graph database applications.

“Neo4j 2.2 is the latest advancement in the Neo4j series. The new Cypher cost-based optimizer and the addition of a new in-memory page cache will greatly improve application read performance and scalability,” said Neo Technology’s CTO, Johan Svensson. “Improvements to the database engine, in particular Neo4j’s new fast write buffering architecture, improves write scaling quite dramatically, both for initial loading of the graph, and for highly concurrent transactional applications.”

Neo4j 2.2 offers overall read and write performance that is up to 10-100 times faster than previous versions, making it the ideal platform for a wide range of applications requiring real-time access to information on data relationships. Today’s release represents an astounding 20+ person years‘ worth of engineering effort on top of Neo4j 2.1, making version 2.2 a significant step forward for Neo4j, as well as the graph database industry as a whole.

“Neo4j has the largest and most vibrant graph database community in the world. This release would not have been possible without a continuous stream of input from community members. Neo4j 2.2 represents our largest beta to date, with participation from more than two thousand users,” said Neo Technology’s VP of Products, Philip Rathle.

Key Neo4j 2.2 Features Include:

  • Massive write scalability – Neo4j 2.2 speeds write throughput significantly across the board, as much as 100 times in certain cases to benefit highly-concurrent applications while leveraging available hardware much more efficiently. This is achieved through faster buffering of updates, and a new unified transaction log that now serves both the graph and its indexes. The results include significant streamlining within the database engine, and efficient leveraging of the underlying hardware’s IO capacity. For the initial import of very large graphs, Neo4j 2.2 introduces a new bulk import utility that can bring data in from external sources at a sustained rate of over 1M records/second — supporting graphs with tens of billions of nodes and relationships.
  • Massive read scalability – The new in-memory page cache increases read throughput by up to 10 times for highly concurrent transactional read applications.
  • Faster Cypher query performance – A new statistics-gathering capability in Neo4j 2.2, together with a new cost-based query optimizer for Neo’s Cypher query language, optimizes queries like never before, as a cost-based optimizer now chooses the best query execution plan using built-in statistics containing information on graph size and shape. Performance improvements in Neo4j 2.2 are as much as 100 times faster in certain cases than in previous versions.
  • Improved developer productivity – Neo4j 2.2 offers improved developer productivity through a number of accompanying tooling improvements:
    • New graph visualization features
    • Query plan visualization
    • New integrated tutorials and learning materials

As Graph Database Adoption Continues to Grow, So Does the Power of Neo4j
Neo Technology continues to address a tremendous need for powerful graph database technology, as Forrester Research analysts have recently reported that graph databases will reach over 25 percent of all enterprises by 2017.1 And according to leading analyst firm, Gartner Inc., “Graph analysis is possibly the single most effective competitive differentiator for organizations pursuing data-driven operations and decisions after the design of data capture.”2 Neo Technology is consistently recognized by Gartner and other leading organizations for its innovation, having being named a Cool Vendor in DBMS, 2014, listed among the ‘Who’s Who in NoSQL DBMSs,’ and included in the 2014 Magic Quadrant for Operational Database Management Systems (DBMS).