Timeplus Proton 3.0 – First Vectorized Streaming SQL Engine
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supportive
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Key features:
First vectorized streaming SQL engine in modern C++ with JIT compilation
High-throughput, low-latency, high-cardinality processing End-to-end streaming: ETL, joins, aggregation, alerts, and tasks
Native connectors: Kafka, Redpanda, Pulsar, ClickHouse, Splunk, Elastic, MongoDB, S3, Iceberg
Native Python UDF/UDAF support to support your AI/ML work loads
The same performance we've proven in large enterprise deployments is now available in the community edition.
Would love feedback from anyone working with streaming data or looking for Flink/ksqlDB alternatives.
Timeplus Proton 3.0, a vectorized streaming SQL engine, is released with enterprise-grade features in its open-source version, sparking interest and discussion among HN users about its capabilities and potential alternatives to existing technologies.
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- 01Story posted
Oct 22, 2025 at 10:32 AM EDT
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Oct 22, 2025 at 11:09 AM EDT
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basically all the cluster nodes are deployed with the same binary with extra configurations.
Built-in S3-based stream storage solves the problem of running separate Stream Processing and Stream Storage solutions and builds on Proton's simplicity.
S3-based state checkpoints as well, both features synergize really well with Proton's strengths.
Congrats on this release and I hope I see more from you soon!
edit: oops I've read the Timeplus release notes that Peter linked, not Proton. Which of the listed features are new in Proton 3.0?
In short, Proton focuses on simplicity — it’s a single-instance engine powerful enough for most common streaming and analytics workflows.
Features like clustering, mutable streams, and S3-based stream storage/state checkpoints are part of the enterprise edition, while Proton keeps the core performance and streaming capabilities in an open-source form.
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