On the Way to Democratized Stream Processing: RisingWave’s Roadmap - RisingWave: Open-Source Streaming Database
Two months ago, we open-sourced RisingWave, a cloud-native streaming database. RisingWave is developed on the mission to democratize stream processing — to make stream processing simple, affordable, and accessible. You may check out our recent blog, document, and source code for more information about RisingWave. Rome was not built in a day, and neither are database systems. We started developing
ksqlDB The database purpose-built for stream processing applications. Real-time Build applications that respond immediately to events. Craft materialized views over streams. Receive real-time push updates, or pull current state on demand. Kafka-native Seamlessly leverage your existing Apache Kafka® infrastructure to deploy stream-processing workloads and bring powerful new capabilities to your app
GitHub - ArroyoSystems/arroyo: Distributed stream processing engine in Rust
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GitHub - gazette/core: Build platforms that flexibly mix SQL, batch, and stream processing paradigms
Gazette makes it easy to build platforms that flexibly mix SQL, batch, and millisecond-latency streaming processing paradigms. It enables teams, applications, and analysts to work from a common catalog of data in the way that's most convenient to them. Gazette's core abstraction is a "journal" -- a streaming append log that's represented using regular files in a BLOB store (i.e., S3). The magic of
Designing a Production-Ready Kappa Architecture for Timely Data Stream Processing
Designing a Production-Ready Kappa Architecture for Timely Data Stream Processing At Uber, we use robust data processing systems such as Apache Flink and Apache Spark to power the streaming applications that helps us calculate up-to-date pricing, enhance driver dispatching, and fight fraud on our platform. Such solutions can process data at a massive scale in real time with exactly-once semantics,
New AWS Lambda controls for stream processing and asynchronous invocations | Amazon Web Services
AWS Compute Blog New AWS Lambda controls for stream processing and asynchronous invocations Today AWS Lambda is introducing new controls for asynchronous and stream processing invocations. These new features allow you to customize responses to Lambda function errors and build more resilient event-driven and stream-processing applications. Stream processing function invocations When processing data
GitHub - infinyon/fluvio: Lean and mean distributed stream processing system written in rust and web assembly.
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ksqlDB: The database purpose-built for stream processing applications.