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You are here: Home / Big Data / SAP Updates Vora Analytics Engine
SAP Updates Vora Query Engine for Better Business Analytics
SAP Updates Vora Query Engine for Better Business Analytics
By Jef Cozza / Data Storage Today Like this on Facebook Tweet this Link thison Linkedin Link this on Google Plus
PUBLISHED:
MARCH
17
2017
Tech giant SAP has announced a series of changes and new tools for the latest release of its SAP Vora solution that it says will help customers accelerate project implementations and offer speed, ease, and affordability to their enterprise business analytics. The announcement was made at Strata + Hadoop World 2017 being held this week in San Jose.

The company also announced that its SAP Cloud Platform Big Data Services (formerly known as Altiscale) expanded its fully managed Hadoop/Spark platform services to Europe. SAP plans to launch Vora on SAP Cloud Platform Big Data Services in the United States and Europe. Vora is an in-memory query engine that applies contextual analytics across data stored in Hadoop, enterprise systems, and other distributed data sources.

Addressing Big Data Needs for Enterprise

"Combining the latest release of SAP Vora with the expanded availability of SAP Cloud Platform Big Data Services into Europe demonstrates that SAP has enterprise-class solutions for a broad range of big data needs," said Greg McStravick, president, database & data management at SAP, in a statement. "SAP Cloud Platform Big Data Services will help enterprises achieve a high-performance, production-ready Hadoop environment with minimal effort, while SAP Vora helps organizations bring big data insights into the enterprise."

The latest version of Vora includes several new built-in capabilities designed to simplify the way businesses run analytics on big data sets. Among the changes is a time series distributed in-memory engine that allows time series data to be stored and analyzed in distributed environments.

SAP said the engine supports highly compressed time series storage and analysis algorithms that work directly on top of the compressed data, providing features such as standard aggregation, granularization, and series analysis using SQL.

Meanwhile, a new graph distributed in-memory engine supports graph processing and helps execute commonly used graph operations, such as pattern matching, shortest path and connected component using SQL, while a distributed in-memory JavaScript Object Notation (JSON) document store supports rich query processing over schema-less JSON data using SQL.

Self-Service Big Data Discovery

"SAP Vora is an enterprise-ready, in-memory distributed computing solution that uses and extends the Apache Spark execution framework to provide interactive analytics on Hadoop," said Dan Vesset, group VP and lead of IDC’s big data and analytics research. "Along with an intuitive web interface, SAP Vora opens up self-service big data discovery to a broader set of users in the organization, making it easier for these insights to be utilized in business decision making.”

The new Vora release also includes other enterprise-class features, including Kerberos support, distributed transaction log for metadata persistence, and built-in currency conversion. The company said that SAP Vora is supported by all major Hadoop vendors including Cloudera, Hortonworks, and MapR for on-premises deployments.

SAP plans to make the SQL capabilities in SAP Vora available in the cloud on SAP Cloud Platform Big Data Services for U.S.-based and Europe-based customers beginning early in the second quarter.

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