DataStax Enterprise 2.0 Now Available With HP Cloud Services
Combination of Apache Cassandra™, Apache Hadoop™, and Apache Solr™ Creates Big Data Platform for Real-Time, Analytics, and Search Data Management
SAN MATEO, Calif., May 10, 2012 /PRNewswire/ -- DataStax, the commercial leader in Apache Cassandra, today announced that DataStax Enterprise 2.0 (DSE 2.0) is now available for HP Cloud Services (http://hpcloud.com). Customers can now run their Big Data workloads on DataStax Enterprise on HP Cloud Services, with operational simplicity and unmatched scalability.
DataStax Enterprise is a complete big data platform, built on Cassandra, architected to manage real-time, analytic, and enterprise search data all in the same cluster. Apache Cassandra™ is an open-source NoSQL distributed database for managing Big Data workloads across multiple data centers with no single point of failure, providing enterprises with continuous availability and performance without compromise.
"With support for multiple data centers, DataStax Enterprise is optimized from the start to help customers move fast to HP Cloud Services," said Michael Shaler, Senior Director of Business Development for DataStax. "Any customer looking to quickly harness the ability to manage Big Data in real-time with Cassandra, perform analytics on that data with Hadoop, and leverage that same data for enterprise search with Apache Solr, now has the option to quickly and cost-effectively scale up with DSE on HP Cloud Services."
With a cloud-ready architecture built for simple, fast deployment, DataStax Enterprise supports customer evolution to public, hybrid and private cloud topologies. DataStax Enterprise is a unique offering in the market – no other vendor provides real-time, analytic, and search capabilities in the same database with the following benefits:
- No single point of failure: Multi-data center support with cloud-ready distributed architecture enables read/write anywhere.
- Linear scalability: DataStax Enterprise's ring node architecture enables performance without compromise, with no special caching layer needed.
- Operational simplicity: DataStax Enterprise supports a dynamic and flexible schema, along with adding new nodes without downtime, and tunable data consistency per operation—all easily accessed and managed in HP Cloud Services.
- DevOps power: DataStax Enterprise supports application development using a familiar SQL-like language, Cassandra Query Language (CQL), as well as integration with cloud management and business intelligence software partners such as RightScale, Pentaho, Datameer, KarmaSphere, WS02 and others.
- One database, many apps: From within a single database cluster, DataStax Enterprise supports broad array of real-time enterprise transactional, analytic and search applications.
DataStax Enterprise for HP Cloud Services includes the following components:
- Production certified Cassandra ready for mission-critical enterprise environments
- Integrated and continuously available Hadoop for analytic tasks
- Integrated and production-ready Solr for enterprise search operations
- Easy visual management and monitoring via OpsCenter
- Expert production support and other services
DataStax offers products and services based on the popular open-source database, Apache Cassandra™, which solve today's most challenging big data problems. DataStax Enterprise combines the performance of Cassandra with analytics powered by Apache Hadoop and enterprise search with Apache Solr, creating a smartly integrated, big data platform. With DataStax Enterprise, real-time, analytic, and search workloads never conflict, giving you maximum performance with the added benefit of only managing a single database.
The company has over 140 customers, including leaders such as Netflix, Disney, Cisco, Rackspace and Constant Contact, and spans verticals including web, financial services, telecommunications, logistics and government. DataStax is backed by industry leading investors, including Lightspeed Venture Partners and Crosslink Capital, and is based in San Mateo, CA.
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