Samza

The easiest way to do batch and streaming data processing. Write once, run anywhere data processing for mission-critical production workloads. Beam reads your data from a diverse set of supported sources, no matter if it’s on-prem or in the cloud. Beam executes your business logic for both batch and streaming use cases. Beam writes the results of your data processing logic to the most popular data sinks in the industry. A simplified, single programming model for both batch and streaming use cases for every member of your data and application teams. Apache Beam is extensible, with projects such as TensorFlow Extended and Apache Hop built on top of Apache Beam. Execute pipelines on multiple execution environments (runners), providing flexibility and avoiding lock-in. Open, community-based development and support to help evolve your application and meet the needs of your specific use cases.

Condense, built by Zeliot, is a real-time data streaming platform that combines fully managed Apache Kafka with everything needed to build and run event-driven applications on top of it. Instead of stitching together Kafka, stream processors, connectors, and observability tools, teams get a single platform: managed Kafka clusters, pre-built and custom transforms, deployment pipelines, and monitoring, all running inside their own cloud account (AWS, Azure, or GCP) so data never leaves their environment. Condense includes Vapr, an autonomous AI supervisor that coordinates specialist agents for Kafka, Kubernetes, Grafana, and coding tasks, cutting the operational load of running streaming infrastructure. Condense is proven in high-throughput production environments, powering connected vehicle platforms, automotive OEM telematics, EV fleets, logistics operations, Travel & Hospitality, Healthcare, Fintech, etc that process billions of events per day.