Managed Cassandra Powered by DataStax Now Available From Rackspace

Rackspace has expanded its data services offerings with the addition of Managed Cassandra powered by DataStax as part of its leading, comprehensive data services portfolio.

Managed Cassandra helps reduce time for deployment, configuration, management and scaling, allowing focus to shift to development productivity – while also gaining access to specialized 24×7 support of Cassandra environments.

Apache Cassandra is an industry standard open-source database used as the backend for a growing number of Internet of Things, web and mobile applications. Cassandra’s decentralized architecture provides support for geographic distribution, low latency operations and management of large amounts of data in a highly fault tolerant environment. Additionally, the SQL-like Cassandra Query Language (CQL) provides a familiar interface for managing and querying data.

While pure Apache Cassandra lacks some analytical, ad-hoc and in-memory functionality of alternate data platforms and Big Data technologies, DataStax has packaged additional features with DataStax Enterprise, closing these gaps and avoiding expensive and redundant database environments or complex Extract, Transform and Load (ETL) management.

Rackspace’s extensive experience working with distributed environments and solutions allows us to understand pain points, requirements and what’s needed to maximize distributed, scalable technologies. Relatively few companies have the know-how to deploy and run Cassandra at scale. We aim to make adoption, scalability and operations easy.

The Managed Cassandra offering includes:

  • Fully Managed Cassandra Solution
    • Experts 24×7 to assist with design, configuration, migrations, scaling, administration, backups, performance tuning and monitoring
    • A one-stop shop for supporting design, architecture, deploying and tuning your DataStax environment
    • Around-the-clock Fanatical Support with consulting services to help you get started and optimize your application and cluster
  • Peer-to-Peer architecture
    • A true distributed, masterless architecture — as opposed to traditional master/slave designs — delivers continuous availability for business-critical web, mobile and IOT applications
  • Application portability
    • Support for RackConnect® and AWS DirectConnect to help minimize the impact of latency while running applications at either Rackspace or AWS data centers, respectively.
  • Custom Configurations
    • Architecture and configurations optimized for Cassandra (highlighted in this fact sheet and reference architecture overview)
    • A solution that scales easily (compared to DIY) allowing you to focus on your application
    • Single-tenant solution provisioned to enable raw performance
    • Support for additional data stores and data processing platforms (e.g., Hadoop, MongoDB, Elasticsearch, Redis)
  • Reduced time-to-market
    • Speed in provisioning and growth planning to keep you competitive

“We’re excited to work with partners like Rackspace because on-premise and cloud deployments are an important combination of data architectures,” said Matt Rollender, VP, Cloud Strategy at DataStax. “With Rackspace, users can deploy modern applications and add DataStax Enterprise capacity to the same cluster with confidence and ease.”

Traditional relational data can then be migrated to Apache Cassandra or DataStax Enterprise, he continued, “without the problems you might encounter with a traditional relational database.”

For additional information on Managed Cassandra and how to sign up for a strategy session with an expert, visit

And see below for a great discussion between Rackspace CTO John Engates and DataStax Co-founder and CTO Jonathan Ellis:

Kyle Hunter was the product marketing manager for ObjectRocket solutions at Rackspace. He is a seasoned IT professional with an long-standing record of driving technical vision, future roadmaps, architecture, strategic planning, software development, product management and product marketing. Kyle’s focus and expertise in new data platforms has positioned him as a go-to resource for users looking to implement large scale data platforms successfully.


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