DataStax Enterprise
The always-on, active everywhere, distributed hybrid cloud database built on Apache Cassandra™
The Only Database Capable of Meeting Today's Demanding Requirements
Best Distribution of Apache Cassandra™
Enterprise-grade, production-certified Cassandra with support from the industry experts. The highest responsiveness and throughput for surges in usage or workloads.
Designed for Hybrid Cloud
One platform—for all types of applications anywhere, any cloud, any model: key-value, graph, tabular, JSON.
Deployment-Ready Advanced Workloads
Fully integrated and optimized database, graph, analytics, in-memory, search, and Kafka—all with a unified security model.
Self-Driving Operational Simplicity
Easily manage DataStax Enterprise like a seasoned professional with features like NodeSync, Upgrade Service, and Traffic Control.
Simplified Modern App Development
Simplified development and deployment for your cloud apps with Kafka and Docker integrations optimized for DataStax Enterprise.
DataStax Enterprise Built For Your Business-Critical Data Assets
DataStax Enterprise makes a lot of claims, but what do they really mean?
“DataStax Enterprise is extremely easy to maintain in operation. From a management perspective, we do not spend a lot of time with the system. One can only describe our experience with Cassandra as ‘effortless’.”
Josep Colom Ikuno
Business Solutions Manager, Kapsch CarrierCom
“We chose DSE because it works at massive scale and has the right security infrastructure in place, and it can operate across multiple clouds rather than being restricted to a certain cloud provider."
Mohammad Khodadadi
Director of Data, Babylon Health
"DataStax Enterprise powers our geospatial search and delivers real time insights to our customers who rely on the most recent data to support their market-level decisions."
David Prinzing
Solutions Architect, Clear CapitalDataStax Enterprise and Apache Kafka™ for Modern Architectures
DataStax Enterprise and Apache Kafka are designed specifically to fit the needs of modern, next-generation businesses. With DataStax Enterprise (DSE) providing the blazing fast, highly-available hybrid cloud data layer and Apache Kafka™ detangling the web of complex architectures via its distributed streaming attributes, these two form a perfect match for event-driven enterprise architectures.
Introducing DataStax Enterprise 6.7 with Amit Chaudhry
DataStax Enterprise 6.7 delivers the leading distribution of Apache Cassandra with multi-workload support for operational analytics, geospatial search, increased data protection in the cloud, better performance insights, Docker production support, and connectivity to Apache Kafka™. Listen to this podcast to learn more!
Enterprise-Ready Features
DataStax Enterprise delivers a wide range of cloud data management, deployment and development capabilities.
Advanced Workloads Pack
For mixed models and complex workloads, you can choose the Advanced Workloads option with DataStax Enterprise to maximize your potential and build modern applications without restraints.
DSE Graph
Get the first graph capabilities powerful enough for customer-facing apps and capable of scaling to massive datasets across data centers and cloud regions.
DSE Analytics
Give your users intelligent and personalized behavior with powerful streaming and batch analytics powered by Apache Spark™.
DSE Search
Help your users easily locate data, with full support for complex queries using sub-string, fuzzy, and full-text search, as well as fast, real-time aggregations, faceting, and filtering.
Deployment Options
DataStax Enterprise by design can be deployed across any type of infrastructure: public or private cloud, on-premises, multi- or hybrid cloud.
Resources
Advanced Performance with DataStax Enterprise
Today’s companies require serious POWER at the data layer if they’re going to thrive in the Right-Now Economy. That’s why DataStax upped the ante with the latest version of its flagship product: DataStax Enterprise (DSE) 6. DSE 6 offers double the performance of DataStax Enterprise 5.1 and has now been independently verified as being at least twice as fast as open source Apache Cassandra. Read this white paper to learn all about DSE 6 performance improvements.
DSE Advanced Performance: Apache Cassandra™ Goes Turbo
Introduction Today, we are very excited to unveil some of the most critical performance enhancements we’ve ever made to DataStax Enterprise (DSE). Enterprise workloads are becoming more and more demanding each day, so we took the opportunity to channel the amazing engineering talent at DataStax to re-architect how we take advantage of compute, memory, and storage. It’s not just about speed, either; we’ve made DSE more efficient and resilient to meet the most demanding workloads. We’ve named our new suite of performance optimizations, utilities, and tools “DataStax Advanced Performance”. The best part? You just need to upgrade to enjoy these out-of-the-box benefits, which include: New thread-per-core and asynchronous architecture, which results in double the read/write performance of open source Apache Cassandra™ Storage engine optimizations that literally slice read/write latencies in open source Cassandra in half Faster analytics that can deliver up to 3x query speed-ups over open source Apache Spark™ DataStax Bulk Loader, which load and unloads data up to 4x faster than current Cassandra load tools Thread-Per-Core and Asynchronous Architecture Apache Cassandra uses a traditional, staged, event-driven architecture (SEDA). With the SEDA architecture, Cassandra assigns thread pools to events or tasks and connects them via a message service. This architecture also uses multiple threads per task, meaning that threads need to be coordinated. Additionally, events in this architecture are synchronous, which can cause contention and slowdowns. Because of this, adding CPU cores eventually sees diminishing returns. DSE 5.1 left, DSE 6 right - With the traditional SEDA architecture, we see much more context switching which is expensive and degrades performance. DSE 6 has a coordination-free design, a thread-per-core architecture which yields incredible performance gains. The whole data layer across DSE, including search, analytics, and graph, benefits from this new architectural change. cassandra-stress, 5 nodes, RF=3, CL=QUORUM, 500GB density Each node in a cluster owns part of the token range; that’s not new. What’s new is that a respective node’s token range is divided evenly among CPU threads: one per CPU core to be exact. A respective thread is now responsible for incoming writes for the part of the token range it owns, and any available thread can be used to handle read requests. This means that evenly distributed data in the cluster results in evenly distributed CPU utilization on a server. This architecture also means that very little coordination is needed between threads, which ensures that a CPU core can be used to its fullest capabilities. cassandra-stress, 5 nodes, RF=3, CL=One, 500GB density Since a single thread owns the writes for its respective token range, what about contention? In DSE 6, we’ve moved reads, writes, and other tasks from synchronous operations to asynchronous. This allows us to eliminate thread contention, always keeping threads working. Combined with the thread-per-core architecture, this allows us to scale performance linearly as we scale the number of CPU cores. This is extremely important as multi-socket motherboards and high core-count cloud instances have become the standard. Storage Engine Optimizations Besides ingesting and serving data faster with thread-per-core, we've also made improvements to the storage engine that improve latency and optimize compaction, which can also be a bottleneck for write-heavy workloads. In DSE 6, that compaction performance is 22% faster than in DSE 5.1 which is already 2x faster than open source Cassandra. We’re also seeing latency improvements of 2x on reads and writes. In DSE 5.1, we introduced 2x compaction performance over Apache Cassandra. In DSE 6, compaction is even faster. 40k fixed throughput test, 3 nodes, RF=3, CL=QUORUM Faster Analytics Scans Also included in DSE Advanced Performance are improved analytics read performance that is 3x over open source Cassandra and Spark. This was made possible by a feature called Continuous Paging, an optimization designed specifically for DataStax analytics queries that scan a large portion of data. We have tested this in a number of scenarios: selecting all columns or some columns, with or without a clustering-column predicate, and in all scenarios we see a 2.5 to 3.5x performance improvement. 3x analytics read performance over open source Spark and Apache Cassandra. DataStax Bulk Loader Also new in DSE 6 is a bulk loader utility that greatly outpaces current Cassandra load/unload utilities. The command line tool handles both standard delimited formats as well as JSON and can load and unload data up to 4x faster than current tools. Conclusion We’re extremely excited for our customers to experience the new Advanced Performance capabilities of DSE 6. With a 2x throughput improvement, massive latency improvements, 10% compaction improvement, a 3x analytics improvement, and a crazy-fast bulk loader, we can’t wait to see the kinds of innovation and disruption our customers will continue to make. To download DSE 6 and for more information on DSE Advanced Performance, check out this page.
