RainStor releases Database 5.5 for Apache Hadoop

RainStor releases Database 5.5 for Apache Hadoop

Summary: RainStor is offering an updated RainStor Database to both improve security for Apache Hadoop-based research and to simplify searching and analysis.

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TOPICS: Big Data
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RainStor recently released RainStor Database 5.5 that is designed to both increase Big Data security and to simplify searching across massive databases.

 

What RainStor has to say about this release

RainStor’s database runs natively on Hadoop and has been deployed by more than 20 global telecommunication providers, 10 multi-national banks and a number of government agencies to significantly reduce cost, complexity and compliance risk when managing Big Data. RainStor partners with industry leaders such as Dell, EMC, HP, and Teradata in addition to Hortonworks, developers of the only 100% open source Hadoop distribution. RainStor is designed for massive scale, runs on the lowest-cost hardware, provides the broadest possible query options including standard SQL, Pig, Hive and MapReduce, and reduces storage footprints by up to 97% through its patented compression technology.

What’s new?

RainStor has added the following to the first-ever enterprise security-grade database for Hadoop:

  • Security:/
    • Data Encryption – Scalable, rapid data encryption at rest to protect massive data volumes
    • Data Masking & Views – New SQL functions to mask sensitive data. When combined with table-level security, these functions ensure that unauthorized users only see masked data
    • Kerberos / LDAP / Active Directory/ PAM support – Standard authorization and authentication capabilities to enable trust within a Hadoop environment.
    • Audit Trail and Tamper-proofing – Built-in auditing functionality to log and track all data changes to meet regulatory compliance requirements
    • Configurable data disposition (with record-level delete) – Efficient deletion of individual records from tables containing trillions of records in clustered environments, enabling efficient data lifecycle management.
  • Search:
    • Faster data exploration through free text search
    • Boost query performance by 10-100X
    • Minimal resource overhead from extremely low (1-5%) index load
    • Extreme scalability by searching across billions of records (multi-petabyte)
    • Simple management with no index sharding.

Analysis

RainStor's goals appear to be to address possible security risks that are associated with Hadoop to analyze "high value" data, that is data that could be the basis for identity theft, fraud or other nefarious activities and to increase the adoption rate of Apache Hadoop by improving its search capabilities.

Banking, financial services and government organizations have been rapidly adopting Apache Hadoop to analyze massive databases containing data that could be the source of big problems if it should get into the wrong hands. RainStor saw an opportunity to add a number of security features to Apache Hadoop to address this issue. Here is a list of what has been added:

  • Users of the RainStor database must be authenticated. 
  • RainStor database adds access controls and polices that control what actions an authenticated user may do
  • An audit layer records what authenticated users are doing and when
  • The data is encrypted to protect the privacy of retained data
  • An "immutability" layer is designed to control what changes can be made to committed data

RainStor points out that this release of its database offers multiple access tools for business query and analysis across petabyte scale data sets running on Hadoop making it a useful tool for a number of different types of access and analysis.

Analysts using RainStor Database can access data using SQL (SQL-92, ODBC/JDBC), MapReduce, Pig and Hive and RainStor's own Lightning Search.

RainStor is one of a number of companies in the Hadoop community trying to enhance and improve the capabilities of Apache Hadoop. Others that should be noted are Cloudara, Cloudspace, DataStax, Greenplum (EMC) IBM,  Intel, MapR Technologies, Pervasive Software, Platform Computing (IBM), Univa and others.

Topic: Big Data

About

Daniel Kusnetzky, a reformed software engineer and product manager, founded Kusnetzky Group LLC in 2006. He's literally written the book on virtualization and often comments on cloud computing, mobility and systems software. In his spare time, he's also the managing partner of Lux Sonus LLC, an investment firm.

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