It has never been more important to leverage multiple fit-for-purpose data stores, combining their unique functionalities to address new and modern business initiatives for organizations.

At the same time, more and more customers are looking to utilize their data for strategic purposes, such as driving measurably better decisions. Data delivers maximum business value when it is contextualized and becomes accessible by any user or application in the organization, and the architecture behind your data is essential to support that accessibility. When implemented correctly, multiple data capabilities — including integration, governance and self-service access — can be woven into a single data fabric architecture that connects data between where it resides and where it needs to be used.

Introducing DataStax Luna

IBM is strengthening its partnership with DataStax to now also offer DataStax Luna — a support offering from DataStax for customers running the Cassandra open-source database environment. With more than 90%  of the Fortune 100 utilizing open-source Cassandra, it’s essential to have the necessary tools for enterprises to solve all their operational and technical problems. That’s where Luna comes in.

DataStax Luna provides 24×7 support for Apache Cassandra versions and an SLA as low as 15 minutes, making sure that you’re covered during those overnight cluster outages and that expert consultation is available for the optimization of your cluster configurations. In addition, DataStax is one of the driving forces behind Apache Cassandra, which means they can provide optimal solutions at a pace necessary for the enterprise. Customers who have engaged with Luna have seen dramatic improvements in recovery times, performance and productivity, completely erasing wait periods for bringing nodes back online, among many other success stories. DataStax Luna is offered in both Professional and Enterprise configurations and with multiple pricing tiers 

Cassandra is optimized for applications needing heavy write workloads, multiple data centers and cloud availability zones. It’s also a strong backbone for addressing real-time analytics and ideal for workloads like IoT, sensor data, messaging applications, personalization engines and fraud detection.

Features of DataStax Luna

DataStax Luna support plans for Cassandra are designed to do the following:

  • Help organizations deliver modern data applications on an open multicloud stack
  • Reduce costs by providing access to experts with deep skills and knowledge
  • Improve ROI, enabling staff to be more nimble in achieving on-time delivery of projects
  • Manage problems and risks of providing support tailored to business requirements

Luna brings enterprise-grade experience on a par with commercial software by expanding traditional support into a customer partnership that provides the following:

  • Certainty that any issue can be resolved, including emergency patching for open source
  • Support for growth without ticket limits
  • A pricing model based on buckets of clusters rather than individual nodes
  • Operational efficiency with best practice check-ins and support for tools and projects in the wider Cassandra ecosystem

IBM open-source database solutions

The DataStax Luna offering is another step forward in a broad set of IBM open-source database solutions including DataStax Enterprise, EDB Postgres Standard, EDB Postgres Enterprise, MongoDB Enterprise Advanced and MongoDB Atlas. Like Apache Cassandra, these market-leading data stores are critically important to customers and need to be accessible as part of the data fabric.  

But the IBM value-add goes broader and encompasses the complete data fabric lifecycle as part of IBM Cloud Pak® for Data, helping ensure data is available throughout the organization in the most efficient and automated way possible. As such, the fabric has three key benefits:

  1. Enable self-service data consumption and collaboration.
  2. Automate governance, protection and security, enabled by active metadata.
  3. Automate data engineering tasks and augment data integration across hybrid cloud resources.

For further information, see the public announcement, this blog and the DataStax with IBM page.


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