Open Source Data Engineering Apps

Open-source, fully-scriptable data ingestion engine that streams events from web, apps, and APIs to any data warehouse in real time.

Postgres-native ETL that streams change data capture in real time to Snowflake, BigQuery, ClickHouse, S3, and Kafka — up to 10x faster than general-purpose pipelines, managed through a familiar Postgres SQL interface.

The dbt-native data observability CLI that turns your existing dbt tests and metadata into anomaly detection, lineage graphs, and Slack/Teams alerts — no separate platform required.

The fastest BI tool for humans and agents — define metrics, models, and dashboards as code and query them instantly on ClickHouse or DuckDB.

A distributed stream processing engine written in Rust that lets you write SQL to run stateful, real-time computations over data streams with subsecond results.

Single C++ binary SQL engine for real-time stream processing, ETL, and analytics on Kafka, Redpanda, and ClickHouse with sub-millisecond latency.

An incremental data indexing engine that keeps AI agent context perpetually fresh by reprocessing only what changed.

Run AI workloads at scale with a Pythonic serverless runtime that handles GPU inference, background jobs, and sandboxes with zero infrastructure overhead.

Drop your files and search them instantly — no vector DB, no indexing pipeline, just raw data queried by a self-evolving intelligence layer.

Visual ETL that compiles to Polars — build pipelines on a canvas, export as standalone Python, and run anywhere without platform lock-in.

Build analytics dashboards, reports, and customer-facing analytics by writing pure SQL — powered by DuckDB and designed for self-hosted deployment.

A next-generation documentation site generator for dbt Core projects — lineage explorer, health scoring, and full-text search for teams without access to dbt Cloud's built-in docs features.

Collaborate on high-quality AI training data with a self-hosted annotation platform built for LLMs, NLP, and multimodal models.

Federated AI search and RAG across 100+ enterprise sources—no data extraction, no vector database required.

A Rust-based real-time data processing engine for AI/ML feature computation, built on Apache DataFusion and Arrow — positioned as an alternative to Flink, Spark, Chronon, and OpenMLDB with unified streaming, batch, and request-time execution.