The Distributed Cloud Database for Hybrid Cloud
The Distributed Cloud Database for Hybrid Cloud
Check out the latest release from the folks at DataStax, whose newest iteration of DSE has major customer-facing updates.
Join the DZone community and get the full member experience.Join For Free
Learn how to migrate and modernize stateless applications and run them in a Kubernetes cluster.
DataStax Enterprise (DSE) 6 represents a major win for our customers who require an always-on, distributed database to support their modern real-time (what we call 'Right-Now') applications, particularly in a hybrid cloud environment. Not only does it contain the best distribution of Apache Cassandra, but it represents the only hybrid cloud database capable of maintaining and distributing your data in any format, anywhere—on-premise, in the cloud, multi-cloud, and hybrid-cloud—in truly data autonomous fashion.
Double the Performance
To start, new functionality designed to make Cassandra more efficient with high-compute instances has resulted in a 2x or more out-of-the-box gain in throughput for both reads and writes. Note that these speed and throughput increases apply to all areas of DSE, including analytics, search, and graph. A new diagnostic testing framework developed by DataStax helped pinpoint performance optimization opportunities in Cassandra, with more enhancements coming in future releases.
Next, DSE 6 includes our first ever advanced Apache Spark integration (over the open source work we've done for Spark in the past) that delivers a number of improvements, as well as a 3x query performance increase.
All of these performance improvements have been designed with our customers in mind so that their Right-Now applications deliver a better-than-expected customer experience by processing more orders, fielding more queries, performing faster searches, and moving more data faster than ever before. If an app's response time exceeds three seconds, it won't be because of DSE.
Self-Driving Operational Simplicity
In designing DSE 6, we listened to both DataStax customers and the Cassandra community. While the interests of these groups sometimes diverge, they do have a few things in common.
It turns out that helping with Cassandra repair operations is a top priority for both. For some, Cassandra repairs aren't a big deal, but for others they are a PITA (pain in the AHEM). Don't get repair right in a busy and dynamic cluster, and it's just a matter of time until you have production-threatening issues.
If you like your current repair setup, keep it. But if you want to eliminate scripting, manual intervention, and piloting repair operations, you can turn on NodeSync and be done. It works at the table level so you have strong flexibility and granularity with NodeSync, plus it can be enabled either with CQL or visually in OpsCenter.
Another area for improvement on which open source users and DataStax customers agree is upgrades. No technical pro that I know looks forward to upgrading their database software, regardless of the vendor used.
These management improvements and others are directly aimed at increasing your team's productivity and letting you focus on business needs vs. operational overhead. The operational simplicity allows even novice DBAs and DevOps professionals to run DSE 6 like seasoned professionals. Ultimately that means much easier enterprise-wide adoption of data management at scale.
Analyze (and Search) This!
For the first time, we're introducing our advanced Spark SQL connectivity layer that provides a new AlwaysOn SQL Engine that automates uptime for applications connecting to DSE Analytics. This makes DSE Analytics even more capable of handling around-the-clock analytics requests, and better support interactive end-user analytics, while leveraging your existing SQL investment in tools (e.g. BI, ETL) and expertise.
We also have great news for analytics developers and others who want to directly query and interact with data stored in DSE Analytics. DataStax Studio 6 provides notebook support for Spark SQL, which means you now have a visual and intelligent interface and query builder that helps you write Spark SQL queries and review the results - a huge time saver! Plus you can now export/import any notebook (graph, CQL, Spark SQL) for easy developer collaboration as well as undo notebook changes with a new versioning feature.
Supporting Distributed Hybrid Cloud
Over 60% of DataStax customers currently deploy DSE in the cloud, which isn't surprising given that our technology has been built from the ground up with limitless data distribution and the cloud in mind. Customers run DSE today on AWS, Azure, GCP, Oracle Cloud, and others, as well as private clouds of course.
DataStax Managed Cloud , which currently supports both AWS and Azure, will be updated to support DSE 6, so all the new functionality in our latest release is available in managed form. Whether fully managed or self-managed, our goal is to provide you with multi and hybrid cloud flexibility that supplies all the benefits of a distributed cloud database without public cloud lock-in.
Yes, There's Actually More...
With DSE 6, we want you to enjoy all the heavy-lifting advantages of Cassandra with none of the complexities and also get double the power. , are now available, so give DSE 6 a try (also now available for non-production development environments via free online training , and other Docker Hub) and let us know what you think.
Published at DZone with permission of Robin Schumacher . See the original article here.
Opinions expressed by DZone contributors are their own.