Splice Machine today announced the release of version 1.5 of its Hadoop RDBMS, adding multiple enterprise-ready features that enable businesses to confidently replace their traditional RDBMSs, such as Oracle® & MySQL™, with an affordable, scale-out alternative that delivers 5-10x greater performance at one fourth the cost.

In working with customers and partners, the Splice Machine team identified key functionality and performance improvements that would enable companies to increase the benefits of using Splice Machine to power real-time applications, run operational data lakes or accelerate their ETL pipelines.

“With its new features, Splice Machine continues to strengthen its position as a viable alternative to the traditional scale-up RDBMS,” said Jack Norris, Chief Marketing Officer, MapR Technologies. “The Hadoop RDBMS running on the enterprise-grade MapR Distribution including Hadoop gives customers a high-performance and massively scalable platform for transactional workloads on real-time data.”

New features included with version 1.5 of Splice Machine’s Hadoop RDBMS include:

  • SQL Compliance
    • Foreign Keys – Enables referential integrity between tables
    • Triggers – Provides the ability to execute procedural code based on update, insert or delete actions
  • BI Tool Compatibility (e.g. Tableau, MicroStrategy)
    • Temporary Tables – Enables BI Tools to create temporary tables to perform operations on intermediate results
    • SQL Functions – Deliver pre-built functions such as TOP N, LIMIT N, MONTHNAME, QUARTER, WEEK and NOW
  • Incremental Backup – Provide recovery from data corruption by backing up data changed since last backup
  • Window Functions – Provide FIRST, LAST, LEAD and LAG functions for advanced analytical queries
  • Performance
    • Enhanced Statistics – Collect more granular statistics required to choose best query plan
    • Cost-Based Optimizer Improvements – Improves ordering of table access, selection of query plans, index selection, join algorithm selection (e.g., broadcast join, merge join, merge sort join, batch nested loop join)
    • Subquery Unrolling – Converts nested subqueries in joins, accelerating certain analytical queries by well over 1000 times

“Unlike many other so-called SQL-on-Hadoop projects, Splice Machine delivers actual enterprise-grade SQL on Hadoop, enabling support of operational applications and analytics, as well as ETL acceleration,” said Dan Woods, Chief Technology Officer, CITO Research. “ETL acceleration is often the first project on Hadoop for many companies. Splice Machine’s transactional capabilities ensure that Hadoop gracefully handles ETL errors and data quality issues without reloading all of the data. Furthermore, Splice Machine can enable incremental ETL that can drive down ETL lag from days to seconds.”

“We’re proud to release version 1.5 of our Hadoop RDBMS as another milestone in the development of our solution,” said Monte Zweben, co-founder and CEO, Splice Machine. “We have added major enterprise-ready features and made significant enhancements to our cost-based optimizer, which dramatically improves performance on analytical queries. In 1.5, we have combined industry standards like SQL and ACID compliance with a modern scale-out architecture – bringing us one step closer to having a single database platform that powers real-time applications and analytics.”

The Splice Machine database is available for licensing at a per node price that includes 24/7 technical support. Version 1.5 is also now available to download and try at www.splicemachine.com/download. For more information about Splice Machine, please visitwww.splicemachine.com.