# feldera/feldera

The Feldera Incremental Computation Engine

Repository: https://github.com/feldera/feldera
Canonical: https://ross.abutalabs.com/products/feldera
Homepage: https://feldera.com
Language: Rust
License: NOASSERTION
License Family: other
Topics: database, rust, sql, streaming, incremental-computation, data-analytics, data-pipelines, incremental-view-maintenance, ivm, materialized-views, real-time
Last push: 2026-08-26T20:12:25+00:00

## Health v2 (maintenance only)
Score: 92/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 99, release rhythm 87, longevity 86
- inputs: {"age_days": 1210, "days_push": 7, "days_rel": 8, "gap_med": 1.0, "n_releases_24m": 295}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2064, forks 149 (observed 2026-08-28T04:06:09.939339+00:00)

## What it is
Feldera is an incremental computation engine written in Rust that evaluates arbitrary SQL programs incrementally using DBSP theory, maintaining materialized views over changing data. It processes inserts, updates, and deletes to SQL tables and updates all dependent views without recomputing from scratch, supporting full SQL semantics including joins, window functions, and recursion.

## Use cases
- keep SQL views fresh over streaming data with incremental view maintenance
- build real-time ETL pipelines in SQL
- run feature engineering pipelines on live and historical data
- power real-time dashboards with millisecond updates
- process datasets larger than RAM incrementally
- replace batch warehouse jobs with continuous incremental analytics

## When to choose
- you need full SQL semantics (joins, aggregates, window functions, recursion) evaluated incrementally
- you want unified batch and streaming compute in one pipeline
- you need high-throughput incremental view maintenance without manual tuning
- your datasets exceed available memory

## When to avoid
- you need a full transactional OLTP database - Feldera is a compute engine, not a database
- you need multi-node fault-tolerant deployments on the open-source edition (that requires the paid Enterprise tier)
- you only run simple periodic batch jobs where incremental computation adds no benefit

## Facets
- artifact type: service
- maturity: active
- function: database, streaming, etl, analytics, search-engine
- domain: databases, analytics, big-data
- platform: rust, self-hosted, cloud
- tags: incremental-view-maintenance, sql, stream-processing, dbsp, materialized-views, data-pipelines, real-time-analytics, data-engineering, real-time, docker, linux, macos

## Member repositories
- feldera/feldera (main) score 92

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:09.939339+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:57:08.563913+00:00, confidence not recorded.
  - readme: https://github.com/feldera/feldera (fetched 2026-08-28T04:06:09.939339+00:00, sha 4cb497833ab6)
  - homepage: https://feldera.com (fetched 2026-08-29T10:37:23.820239+00:00, sha b9b1fa252c36)
  - site_page: https://docs.feldera.com/ (fetched 2026-08-29T10:37:23.829733+00:00, sha f52a16febad4)
  - site_page: https://www.feldera.com/about-us (fetched 2026-08-29T10:37:23.831867+00:00, sha 2d4ad9f16ae9)
  - site_page: https://docs.feldera.com/get-started (fetched 2026-08-29T10:37:23.835166+00:00, sha a85a3b66b488)
  - site_page: https://www.feldera.com/pricing (fetched 2026-08-29T10:37:23.837144+00:00, sha 45e131faced3)
- Data as of 2026-08-30T08:39:29.467469+00:00.