Project Metamorphosis: Unveiling the next-gen event streaming platformLearn More

Confluent Platform and DataStax

Confluent Platform and DataStax Enterprise Together for a Modern Datacenter

Managing the velocity and variety of data with an event driven, enterprise architecture
The world’s largest enterprises combine Confluent Platform and DataStax’s distributed database to deliver the industry’s highest throughput and most resilient microservices architecture.

DataStax data management platforms are built on Apache Cassandra and optimized for distributed data, zero downtime and high performance at scale. DataStax makes it easier for companies to deploy, manage and secure enterprise-grade applications in hybrid and multi-cloud environments, while maintaining full control of their data.

Why DataStax and Confluent Platform?

  • Enterprise Proven Scalability and Resiliency

    Confluent Platform and DataStax database platforms replicate data across machines for geo-distributed scalability and fault tolerance during infrastructure outages

  • Microservices Development Enabled

    Confluent Platform is the best streaming solution to stitch together event driven data and DataStax Enterprise is the optimal database to serve data for real-time, contextual applications delivering the ideal technology combination for microservices

  • Multi-workloads with Advanced Security and High Performance

    Confluent Platform and DataStax Enterprise are architected from the ground up to satisfy modern, rapid traffic workloads, all while achieving enterprise-grade security compliance

  • Flexibility and Choice

    Confluent Platform and DataStax Enterprise enable scale in any environment; single cloud, hybrid cloud, multi cloud, or on-premises

Confluent and DataStax Integration

Confluent and the DataStax team have partnered to deliver the DataStax Apache Kafka™ Connector that automatically moves data from Kafka and Confluent Platform at high-speed ingest rates to DataStax Enterprise (DSE) and DataStax Distribution of Apache Cassandra.

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