Splice Machine Announces Version 2.0 of its RDBMS: A Hybrid In-Memory Architecture Powered by Hadoop and Spark
Revolutionary relational database leverages the in-memory technology of Apache Spark and massive scale of Hadoop to power operational applications and real-time analytics
San Francisco, CA – November 17, 2015 – Splice Machine today announced the 2.0 version of its RDBMS, the first hybrid in-memory RDBMS powered by Hadoop and Spark. Splice Machine’s version 2.0 delivers a database solution that incorporates the proven scalability of Hadoop, ANSI SQL, ACID transactions, and the in-memory performance of Spark. The new, flexible hybrid database enables businesses to perform simultaneous OLAP and OLTP workloads and increase performance over traditional RDBMS, such as Oracle® & MySQL™, by 10-20X at one-fourth the cost. Splice Machine is now accepting applications to test the public beta of its version 2.0 product.
Splice Machine 2.0 integrates Apache Spark, a fast, open source engine for large-scale data processing, into its existing Hadoop-based architecture. Splice Machine 2.0 has the following benefits:
- Transactional SQL – Supports existing OLTP applications without rewrites of existing SQL or retraining of developers
- Scale-Out Architecture – Cost-effectively scales out on commodity hardware with proven technology from Hadoop and Spark
- In-Memory Technology – Achieves outstanding performance for OLAP queries with in-memory technology from Spark
With the addition of Spark, Splice Machine 2.0 delivers high performance for mixed OLTP and OLAP workloads. It is ideal for a variety of use cases, including: digital marketing, ETL acceleration, operational data lakes, data warehouse offloads, IoT applications, web, mobile, and social applications, and operational applications.
The Splice Machine RDBMS is an innovative hybrid of in-memory technology from Spark and disk-based technology from Hadoop. Unlike in-memory only databases, the Splice Machine RDBMS does not force companies to put all of their data in-memory, which can become prohibitively expensive as data volume grows. It uses in-memory computation to materialize the intermediate results of long-running queries but uses the power of HBase to durably store and access data at scale.
“By delivering an affordable, fully operational platform that is designed to support OLTP and OLAP workloads concurrently, Splice Machine 2.0 offers a unique and powerful way for businesses to perform real-time analytics and operational queries together without sacrificing performance or breaking the bank,” said Charles Zedlewski, Vice President, Products at Cloudera. “As more customers start to run Spark on Cloudera’s platform, Splice Machine’s integration complements the analytical capabilities of our enterprise data hubs, enabling customers across a variety of industries to handle all types of workloads with greater efficiency.”
Splice Machine 2.0 includes advanced resource management to ensure high-performance for simultaneous OLTP and OLAP queries. With separate processes and resource management for Hadoop and Spark, the Splice Machine RDBMS can ensure that large, complex OLAP queries do not overwhelm time-sensitive OLTP queries. Users can set custom priority levels for OLAP queries to ensure that important reports are not blocked behind a massive batch process that consumes all cluster resources.
“The financial services industry has seen exponential increases in the volume and variety of data that shows no sign of relenting, causing us to look for new architectures that can simultaneously support both operational and analytical workloads,” said Jesse Lund, Head of R&D for Wells Fargo. “We are impressed with the Splice Machine 2.0 hybrid architecture and are excited to put it to the test.”
With Spark, the Splice Machine RDBMS adds an extensive management console. Users can use it to monitor queries in process and visualize each step in the execution pipeline. This includes monitoring of batch import processes, with the ability to see import errors in real-time.
Splice Machine’s 2.0 version of its Hadoop RDBMS is a game changer,” said Dr. Robin Bloor, Chief Analyst and Co-Founder, The Bloor Group. “By leveraging the immense scale-out power of Hadoop and the powerful in-memory speed of Spark, businesses can combine analytical and operational systems on one scale-out database without sacrificing performance, eventually performing transactions only when needed.”
The new architecture includes the ability to easily access external data and libraries. The Splice Machine RDBMS can execute federated queries on data in external databases and files using Virtual Table Interfaces (VTIs). It can also execute all pre-built Spark libraries (over 130 and growing) for machine learning, stream analysis, data integration and graph modeling.
“We’re proud to release Splice Machine 2.0, the first, affordable hybrid in-memory RDBMS powered by Hadoop and Spark, as a major milestone in the development of our solution,” said Monte Zweben, co-founder and CEO, Splice Machine. “By combining industry standards like SQL and ACID compliance with a modern scale-out architecture integrated with Spark, we are now able to offer a single database platform that is unique in its ability to simultaneously power applications and analytics.”
Splice Machine is currently looking for testers for the public beta of its 2.0 RDBMS. To become a tester, or to gain more information, please visit https://www.splicemachine.com/product/v2-beta-program/.
About Splice Machine
The Splice Machine RDBMS is the first hybrid, in-memory RDBMS powered by Hadoop and Spark. Leveraging in-memory technology from Spark and scale-out capabilities from Hadoop, Splice Machine can replace Oracle® and MySQL™ databases, while increasing performance by 10-20x at one-fourth the cost. With an innovative, hybrid architecture and advanced resource isolation, the Splice Machine RDBMS provides exceptional performance for simultaneous OLAP and OLTP workloads, enabling companies to unlock the insights in their Big Data to make decisions in the moment.