Ross ROSS = Recommend OSS · open-source software intelligence for agents

timeplus-io/proton

The Fastest Unified Streaming SQL Engine in a Single C++ Binary. ⚡ Millisecond latency. 100+ GB/s throughput. Continuously compute real-time context from streams, logs, metrics, events, and CDC. observed · 2026-08-28

github.com/timeplus-io/proton · homepage · C++ · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

93/100

  • Activity 97
  • Release rhythm 96
  • Longevity 79
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 11.0
  • age_days: 1115
  • days_rel: 31
  • days_push: 21
  • n_releases_24m: 45

Full methodology

Adoption not part of the score

2247 stars · 110 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Timeplus Proton is a unified streaming SQL engine shipped as a single dependency-free C++ binary, built on the ClickHouse engine. It ingests from sources like Kafka, ClickHouse, Postgres, and S3/Iceberg, and continuously computes real-time analytics via streaming SQL, materialized views, joins, and alerting.

Use cases

  • run streaming SQL queries over Kafka topics in real time
  • build real-time analytics dashboards with millisecond latency
  • process CDC events from databases into materialized views
  • monitor logs and metrics with continuous SQL pipelines
  • replace Apache Flink or ksqlDB without JVM overhead
  • create real-time context feeds for AI agents
  • ingest and transform streaming data into ClickHouse or Iceberg

When to choose

  • you need high-throughput stream processing with a single zero-dependency binary
  • you want SQL-first streaming ETL instead of writing Flink or Kafka Streams code
  • you need millisecond-latency analytics on event streams, logs, or CDC data
  • you want native connectors to Kafka, ClickHouse, Postgres, and Iceberg in one engine

When to avoid

  • you need batch-only analytics with no streaming requirements
  • you require a JVM ecosystem with Flink's extensive connector and state backend options
  • you need a fully managed distributed cluster with built-in coordination out of the box

Facets

application · maturity active

streaming etl search-engine monitoring alerting database analytics big-data monitoring developer-tools self-hosted cpp cli stream-processing streaming-sql clickhouse kafka materialized-views cdc single-binary flink-alternative ksqldb-alternative real-time-analytics sql data-engineering real-time linux macos docker

2 sources

Member repositories

RepositoryRoleHealth v2
timeplus-io/protonmain93

For agents

markdown · JSON · MCP: product_card(name="timeplus-io/proton")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem