All Open Source Apps

Define, schedule, and monitor complex data workflows as Python code — with a powerful UI, 80+ provider integrations, and battle-tested scalability across thousands of production deployments.

Distributed SQL database for real-time analytics at scale

Open-source ELT platform with 600+ connectors for moving data from any source to warehouses, lakes, and AI agents.

Open-source backend platform with Auth, Databases, Storage, Functions, Messaging, Realtime, and Sites — deploy via Docker or use Appwrite Cloud.

Open-source BI tool with drag-and-drop dashboards, 20+ data source connectors, and AI-powered natural language queries — a self-hosted alternative to Tableau.

Open-source enterprise data warehouse unifying analytics, vector search, full-text search, and AI agent orchestration in a single Rust-built engine on S3.

Event-driven orchestration platform for data, AI, and infrastructure workflows — define everything in YAML, run anywhere at scale.

Open-source vector database and search engine built in Rust for production-grade AI applications — from semantic search to RAG pipelines and recommendation systems.

Redash lets anyone connect to 35+ SQL and NoSQL data sources, write a query in the browser, and turn the result into a shared dashboard — no separate BI suite required.

A high-performance, open-source time-series database built for financial market data, IoT telemetry, and real-time analytics, combining a zero-GC Java/C++ core with SIMD-accelerated SQL and a WAL-to-Parquet storage engine.

Open-source, embedded vector database built on the Lance columnar format for fast multimodal search across billions of vectors, backed by Y Combinator (W23).

Open-source GenBI engine that lets AI agents turn natural-language questions into governed SQL, charts, and shareable dashboards across 20+ data sources — no vendor lock-in, no black-box prompts.

Open-source no-code platform to build databases, apps, automations, and AI agents — self-hosted or cloud, with full data ownership.

A reactive Python notebook that eliminates hidden state, runs reproducibly, and deploys as a web app or script — stored as pure Python, built for the AI era.

Born out of Y Combinator's S2023 batch, ParadeDB is a Postgres extension that delivers Elasticsearch-quality BM25 search and real-time analytics without a separate search cluster to manage.

Fast, lightweight, schema-less search backend in Rust — microsecond queries, 30MB RAM, no document storage required.

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

A temporal, verifiable graph database with git-like branching, integrated vector/text/geo search, and RDF/SPARQL/JSON-LD/openCypher support — benchmarked at 10.4x faster than the next database on the full Wikidata dump.

Embedded KV store built on object storage with zero replication cost

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.

A graph-vector database built from scratch in Rust that unifies graph traversal, vector search, key-value, and relational storage into a single platform for AI applications.

An open-source context database that gives AI agents a unified filesystem for memory, resources, and skills with hierarchical tiered retrieval.

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.