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

jitsucom/jitsu

Jitsu is an open-source Segment alternative. Fully-scriptable data ingestion engine for modern data teams. Set-up a real-time data pipeline in minutes, not days observed · 2026-08-28

github.com/jitsucom/jitsu · homepage · TypeScript · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

97/100

  • Activity 99
  • Release rhythm 92
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: 23
  • age_days: 2220
  • days_rel: 55
  • days_push: 7
  • n_releases_24m: 12

Full methodology

Adoption not part of the score

5043 stars · 395 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Jitsu is an open-source, self-hostable event data platform and Segment alternative that collects event data from websites, apps, and servers and delivers it to data warehouses like ClickHouse, BigQuery, Snowflake, and Redshift in real time. It supports JavaScript transformation functions, identity stitching, deduplication, automatic schema management, and an MCP server, deployable via Kubernetes or Jitsu Cloud.

Use cases

  • collect website and app event data into a data warehouse in real time
  • self-host a Segment alternative to avoid vendor lock-in and usage billing
  • stream user behavioral events to ClickHouse with sub-second delivery
  • transform, filter, and enrich events with JavaScript functions before delivery
  • stitch anonymous and identified user identities automatically
  • replace Google Analytics-style tracking with warehouse-first event collection
  • deduplicate and buffer events during warehouse downtime

When to choose

  • you want an MIT-licensed, self-hostable Segment/CDP alternative
  • you need real-time or micro-batch delivery to warehouses instead of daily batch loads
  • you want event transformations via JavaScript functions with persistent storage and HTTP fetch
  • your stack targets ClickHouse, BigQuery, Snowflake, Redshift, Postgres, or S3
  • you need identity stitching and deduplication without writing SQL

When to avoid

  • you only need batch ELT from SaaS APIs rather than event streaming
  • you cannot run Kubernetes, since the feature-complete deployment requires a cluster
  • you need a fully managed solution and don't want any infrastructure to operate (though Jitsu Cloud exists)
  • you need deep prebuilt BI dashboards rather than raw event delivery to a warehouse

Facets

service · maturity active

etl streaming webhook api-framework self-hosted analytics analytics big-data databases web-development self-hosted self-hosted cloud go customer-data-platform segment-alternative event-tracking data-pipeline clickhouse data-warehouse event-collection cdp data-engineering docker kubernetes web-server nodejs

10 sources

Member repositories

RepositoryRoleHealth v2
jitsucom/jitsumain97

For agents

markdown · JSON · MCP: product_card(name="jitsucom/jitsu")

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