Awesome Data Engineering

A web service that makes it easy to quickly and cost-effectively process vast amounts of data.

A light-weight engine for general-purpose data processing including both batch and stream analytics. It is based on a novel unique data model, which represents data via functions and processes data via columns operations as opposed to having only set operations in conventional approaches like MapReduce or SQL.

A cloud-based platform deployed on Kubernetes making Apache Spark more developer-friendly and cost-effective.

Pure-Go classic machine learning toolkit and data engineering utilities. Eight algorithms with zero external dependencies.

Connecting Apache Spark with different data stores. Deprecated.

A free & cross platform monitoring tool (Spark UI / Spark History Server alternative).

Personal genome analysis toolkit with Python scripts analyzing raw DNA data across 17 categories (health risks, ancestry, pharmacogenomics, nutrition, psychology, etc.) and generating a terminal-style single-page HTML visualization.

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage.

An iterative graph processing system built for high scalability.

A machine learning platform that enables data scientists and app developers to easily create intelligent apps at scale.

Fast scalable machine learning API for smarter applications.

A software framework for easily writing applications which process vast amounts of data (multi-terabyte data-sets) - in-parallel on large clusters (thousands of nodes) - of commodity hardware in a reliable, fault-tolerant manner.

Data warehouse software facilitates querying and managing large datasets residing in distributed storage.

Scalable machine learning library for Hive/Hadoop.

The REST Spark Server.

An environment for quickly creating scalable performant machine learning applications.

A distributed SQL query engine designed to query large data sets distributed over one or more heterogeneous data sources.

Python interface to Hive and Presto.

A multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters.

Apache Spark's API for graphs and graph-parallel computation.

Spark's scalable machine learning library consisting of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, as well as underlying optimization primitives.

A community index of packages for Apache Spark.

Examples by Zhen He.

A cloud native data pipeline and transformation toolkit written in Go.

An application framework which allows for a complex directed-acyclic-graph of tasks for processing data.

Open source Master Data Management platform using machine learning for entity resolution at scale. Native to Databricks, Microsoft Fabric, Snowflake, AWS, and GCP. Golden records are maintained through a persistent Zingg ID across all systems and sources.

A guide to designing an Apache Iceberg lakehouse from scratch.

This blog offers a curated list of top data science books, categorized by topics and learning stages, to aid readers in building foundational knowledge and staying updated with industry trends.

A fast, friendly guide to integrating large language models into your data workflows.

A practical introduction to data engineering on the Snowflake cloud data platform.

Agentic AI platform to connect any database (PostgreSQL, MySQL, MongoDB, etc.) and query in plain English; includes self-refreshing intelligent dashboards and action workflows triggered by data changes.

A modern, enterprise-ready business intelligence web application.

D3-based reusable chart library.

A JavaScript library for manipulating documents based on data.

D3's simpler, easier to use cousin. Mostly predefined templates that you can just plug data in.

Open-source SQL to map platform for BigQuery, Snowflake, and PostGIS.

A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application.

Open-source analytics notebook for reusable SQL workflows, interactive reports, and AI-assisted data exploration.

The easy, open source way for everyone in your company to ask questions and learn from data.

Flask, JS, and CSS boilerplate for interactive, web-based visualization apps in Python.

A pure-python graphics and GUI library built on PyQt4 / PySide and numpy. It is intended for use in mathematics / scientific / engineering applications.

Python helpers for building dashboards using Flask and React.

Natural language database query interface with automatic chart generation, supporting Chinese and English queries.

Make Your Company Data Driven. Connect to any data source, easily visualize and share your data.

A Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.

A JavaScript Charting Library for Streaming Data.

Open-source, self-hosted, warehouse-native product analytics. Runs funnels, retention, and paths directly on DuckDB, Postgres, Snowflake, or ClickHouse.

Fast JavaScript charts for any data set.

The first technical conference that bridges the gap between data scientists, data engineers and data analysts.

A Python library that facilitates the comparison of two DataFrames in Pandas, Polars, Spark and more. The library goes beyond basic equality checks by providing detailed insights into discrepancies at both row and column levels.

Data Validation Tool compares data from source and target tables to ensure that they match. It provides column validation, row validation, schema validation, custom query validation, and ad hoc SQL exploration.

Python SDK that dispatches parallel web-research agents across

A high-performance Python library for comparing large datasets (CSV, Parquet) locally using Rust and Polars. It features zero-copy streaming to prevent OOM errors and generates interactive HTML data quality reports.

Open source repository of web crawl data.

The world's most comprehensive authoritative data source knowledge base. 160+ curated sources from governments, international organizations, and research institutions with MCP integration.

GitHub's public timeline since 2011, updated every hour.

Synthetic financial savings behavior generator for Latin America: users, savings goals, and transactions calibrated on 506K real records (2015–2024). Reproducible by seed, 100% synthetic.

42-table synthetic SME dataset with double-entry accounting, tax compliance (AU/US/UK), and temporal realism. CSV, SQL, Parquet, SQLite. Ideal for ETL pipeline testing.

A 30-metro composite of US household cost burdens (housing, taxes, childcare, healthcare, transport) aggregated from Census ACS, BLS Consumer Expenditure Survey, and HUD Fair Market Rents. Open methodology, free, no email gate.

Wikipedia's complete copy of all wikis, in the form of Wikitext source and metadata embedded in XML. A number of raw database tables in SQL form are also available.

Open-source data integration for modern data teams.

An open-source distributed pub-sub messaging system.

A tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.

High-speed CLI tools for database export, import, replication and migration with parallel streaming to CSV, Parquet, JSON and cloud storage, supporting PostgreSQL, MySQL, Oracle, SQL Server and 80+ sources.

Real-time data ingestion tool leveraging change data capture.

Utility belt to handle data on AWS.

A fully managed, cloud-based service for real-time data processing over large, distributed data streams.

Change data capture from PostgreSQL into Kafka. Deprecated.

Context-Aware RAG Processing Queue for high availability and adaptive rate-limiting.

Conflict-free merge for DataFrames, JSON, ML models & distributed agents — powered by CRDTs.

A real-time B2B data API for company and people intelligence, providing firmographics, headcount signals, job listings, web traffic, and funding events via REST API and webhooks for data enrichment pipelines.

A delimited data preboarding framework that fills the gap between MFT and the data lake.

High-performance, streaming-first ETL engine for Node.js and TypeScript with constant memory footprint.

Managed cloud object storage transfers for ingestion workflows.

Data ingestion engine that connects 400+ Singer taps to Parquet files in cloud buckets (S3, GCS, Azure). Streaming, incremental, with auto-catalog.

Lightweight Node.js ETL framework for databases → data lakes/warehouses.

self-hosted database migration and change data capture (CDC) tool with built-in SQL IDE.

A fast&simple pipeline building library for Python data devs, runs in notebooks, cloud functions, airflow, etc.

OSS Reverse ETL CLI. Sync data from warehouses to business tools via YAML.

Local-first, open-source desktop ETL/ELT studio: drag a pipeline onto a canvas (or describe it to a built-in on-device AI assistant) and run it at native speed through DuckDB. 290+ connectors, a scheduler, and an MCP server for driving pipelines from an LLM. No cloud, no servers.

An open source bulk data loader that helps data transfer between various databases, storages, file formats, and cloud services.

CLI tool to enrich CSV files with company data (financials, contacts, metadata) from 250M+ company records. Available on npm.

Managed event ingestion service that converts JSON sent to a REST API into Hive-partitioned Parquet on Cloudflare R2, queryable from DuckDB, ClickHouse, BigQuery, Snowflake, and Python.

No/low-code data pipeline platform that handles both batch and real-time data ingestion.

An open source data collector for unified logging layer.

Universal data ingestion framework for Hadoop from LinkedIn.

Live import all your Google Sheets to your data warehouse.

Data Acquisition and Processing Made Easy. Deprecated.

CLI tool to copy data between databases with a single command. Supports 50+ sources including PostgreSQL, MySQL, MongoDB, Salesforce, Shopify to any data warehouse.

Publish-subscribe messaging rethought as a distributed commit log.

Kafka in Docker.

Kafka-winston logger for Node.js from Uber.

A tool for managing Apache Kafka.

Node.js client for Apache Kafka 0.8.

Generic command line non-JVM Apache Kafka producer and consumer.

Simplified command-line administration for Kafka brokers.

Polyglot document intelligence library with a Rust core and bindings for Python, TypeScript, Go, and more. Extracts text, tables, and metadata from 62+ document formats for data pipeline ingestion.

A Kafka Proxy, solving problems like encrypting your Kafka data at rest.

The Apache Kafka C/C++ library.

Crawlee-based actor extracting structured LinkedIn job listings at scale without API keys.

CLI & code-first ELT.

An open source event messaging platform that provides a REST API on top of Kafka-like queues.

Python PDF-to-Markdown orchestrator. Classifies each page and routes to the optimal backend (PyMuPDF, Docling, RapidOCR, Gemini Flash), emitting Markdown plus a per-page confidence score so ingestion pipelines can quarantine low-trust pages before feeding LLMs or retrieval.

A PostgreSQL extension to produce messages to Apache Kafka.

Provides a new storage abstraction - a stream - for continuous and unbounded data.

Robust messaging for applications.

Open-source self-hosted analytics pipeline that lands raw events as Parquet in your own object storage. Uses NATS JetStream for durable buffering and BigQuery external tables for querying. Designed for teams that want to own their raw event data.

Pinterest's Kafka to S3 distributed consumer.

The fastest way to build custom data extractors and loaders compliant with the Singer Spec.

CLI data integration tool specialized in moving data between databases, as well as storage systems.

Real-time X (Twitter) data extraction platform with REST API (76 endpoints), 20 bulk extraction tools, account monitoring, HMAC-signed webhooks, and MCP server for AI agent integration.

FlightPath is a gateway to a data lake's bronze layer, protecting it from invalid external data file feeds as a trusted publisher.

An open-source, unified metadata management for data lakes, data warehouses, and external catalogs.

A modular Data Lakehouse platform that simplifies the management and monitoring of Apache Spark clusters across Kubernetes and Hadoop environments.

An open source platform that delivers resilience and manageability to object-storage based data lakes.

A Transactional Catalog for Data Lakes with Git-like semantics. Works with Apache Iceberg tables.

Managed lakehouse platform on Apache Iceberg with DuckDB query compute, S3 storage, Postgres wire protocol, and SQL transforms.

The DataProfiler is a Python library designed to make data analysis, monitoring, and sensitive data detection easy.

An open-source data profiler specifically focused on discovery and validation of complex patterns in data.

A general-purpose open-source data profiler for high-level analysis of a dataset.

A database for user interactions (likes, views, follows) represented as graphs, with precomputed reads served in real-time.

A numeric time-series database. It can be used to capture, store and process time-series data in real-time. The word "akumuli" can be translated from esperanto as "accumulate".

Makes it easy to set up, operate, and scale a relational database in the cloud.

An open source, distributed, in-memory database for scale-out applications.

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values.

Open-source multi-model database with native graph, document, key-value, and vector support. SQL, Cypher, and Gremlin query languages. Apache 2.0 license.

A fast and flexible NoSQL database service for all applications that need consistent, single-digit millisecond latency at any scale.

A fast, fully managed, petabyte-scale data warehouse that makes it simple and cost-effective to analyze all your data using your existing business intelligence tools.

A distributed system designed to ingest and process time series data.

The right choice when you need scalability and high availability without compromising performance.

This simple form allows you to try out different values for your Apache Cassandra cluster and see what the impact is for your application.

An open-source graph database. Google.

A script to easily create and destroy an Apache Cassandra cluster on localhost.

Embedded ClickHouse — full ClickHouse SQL dialect, ~80 data formats, and 12+ source connectors (S3, Postgres, MongoDB, Kafka, Iceberg) in core. Python, Go, Rust, Node, Bun, Zig, and Ruby bindings.

Distributed columnar DBMS for OLAP. SQL.

The highest performing NoSQL distributed database.

Scalable SQL database with the NOSQL goodies.

Fast distributed metrics database.

The fully transactional, cloud-ready, distributed database.

Column oriented distributed data store ideal for powering interactive applications.

A fast in-process analytical database that has zero external dependencies, runs on Linux/macOS/Windows, offers a rich SQL dialect, and is free and extensible.

Search & Analyze Data in Real Time.

Distributed. Columnar. Versioned. Streaming. SQL.

A distributed, fault-tolerant graph database by Twitter. Deprecated.

A large-scale graph database.

The Greenplum Database (GPDB) - An advanced, fully featured, open source data warehouse. It provides powerful and rapid analytics on petabyte scale data volumes.

The Hadoop database, a distributed, scalable, big data store.

A scalable time series database based on Cassandra and Elasticsearch, by Spotify.

A scalable, searchable key-value store. Deprecated.

Scalable datastore for metrics, events, and real-time analytics.

A key-value store for microcontroller and IoT applications.

Fast scalable time series database.

A lightweight network server on top of the Kyoto Cabinet key-value database, built for high-performance and concurrency.

An enhanced, drop-in replacement for MySQL.

Distributed Transactional In-Memory Database (based on MongoDB).

An open-source, document database designed for ease of development and scaling.

The world's most popular open source database.

Pinterest MySQL Management Tools.

The world's leading graph database.

Typed graph database where agents branch and merge like Git. S3-native, Rust, traversal + vector + BM25 in one runtime.

A scalable, distributed Time Series Database.

2nd Generation Distributed Graph Database with the flexibility of Documents in one product with an Open Source commercial friendly license.

Percona Server for MongoDB® is a free, enhanced, fully compatible, open source, drop-in replacement for the MongoDB® Community Edition that includes enterprise-grade features and functionality.

A free, open source, complete online backup solution for all versions of Percona Server, MySQL® and MariaDB®.

The world's most advanced open source database.

A relational column-oriented database designed for real-time analytics on time series and event data.

Fully Transactional NoSQL Document Database.

An open source, BSD licensed, advanced key-value cache and store.

The open-source database for the realtime web.

A time-series object store for Cassandra that handles all the complexity of building wide row indexes.

A distributed database designed to deliver maximum data availability by distributing data across multiple servers.

Riak TS is the only enterprise-grade NoSQL time series database optimized specifically for IoT and Time Series data.

Managed PostgreSQL with pgvector for AI workloads. HNSW indexing, sub-4ms latency, and built-in SQL editor with automatic embedding generation.

Replicated SQLite using the Raft consensus protocol.

NoSQL data store using the seastar framework, compatible with Apache Cassandra.

In-process analytical SQL database written in C++20. Reads Parquet, CSV, JSON, Avro, Arrow, SQLite, and Excel directly. Single binary, Python package, and 1.3 MB WASM build for the browser.

OLTP + OLAP Database built on Apache Spark.

A high performance NoSQL database supporting many data structures, an alternative to Redis.

An in-memory database and application server.

A distributed NewSQL database compatible with MySQL protocol.

A time series database application that provides secure access to time series data based on Accumulo and Grafana.

Built as an extension on top of PostgreSQL, TimescaleDB is a time-series SQL database providing fast analytics, scalability, with automated data management on a proven storage engine.

A scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster.

Distributed, MPP columnar database with extensive analytics SQL.

An embedded vector database for on-device RAG and edge AI, the SQLite of vector databases.

Analyzes resource usage and performance characteristics of running containers.

Easily manage Docker containers & their data.

Package golang service into minimal Docker containers.

Visualize Docker images and the layers that compose them.

Application Containers for Masses.

Docker microservice for saving/restoring volume data to S3.

A cluster manager, designed for both long-lived services and short-lived batch processing workloads.

RancherOS is a 20mb Linux distro that runs the entire OS as Docker containers.

Docker composition tool with idempotency features for deploying apps composed of multiple containers. Deprecated.

Weaving Docker containers into applications.

A lightweight tool for easy deployment and rollback of dockerized applications.

A highly configurable Logstash (1.4.4) - Docker image running Elasticsearch (1.7.0) - and Kibana (3.1.2).

JDBC importer for Elasticsearch.

PostgreSQL Extension that allows creating an index backed by Elasticsearch.

A memory-centric distributed storage system enabling reliable data sharing at memory-speed across cluster frameworks, such as Spark and MapReduce.

Object storage built to retrieve any amount of data from anywhere.

A unified, distributed storage system designed for excellent performance, reliability, and scalability.

Gluster Filesystem.

A distributed file system designed to run on commodity hardware.

A high-performance Cloud-Native file system driven by object storage for large-scale data storage.

Software Defined Storage is a distributed, parallel, scalable, fault-tolerant, Geo-Redundant and highly available file system.

Orange File System is a branch of the Parallel Virtual File System.

A file system that stores all its data online using storage services like Google Storage, Amazon S3, or OpenStack.

Seaweed-FS is a simple and highly scalable distributed file system. There are two objectives: to store billions of files! to serve the files fast! Instead of supporting full POSIX file system semantics, Seaweed-FS choose to implement only a key~file mapping. Similar to the word "NoSQL", you can call it as "NoFS".

Utils for streaming large files (S3, HDFS, gzip, bz2).

A bite-sized, lightweight HDFS compatible file system built over Cassandra.

A pure python HDFS client.

Fault-tolerant distributed file system for all storage needs.

News, tips, and background on Data Engineering.

Subreddit focused on ETL.

Job board focused on AI, ML, and data engineering roles with 7,400+ listings, salary data, and a free REST API.

Interviews with AI and data infrastructure leaders on building production systems.

The show about modern data infrastructure.

Technical deep dives on AI engineering, from model training to deployment.

Making AI practical, productive, and accessible to everyone.

Daily interviews about technical software topics, including data infrastructure.

How analytics engineers build and maintain data pipelines at scale.

A show where they talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.

Simple server that scrapes HAProxy stats and exports them via HTTP for Prometheus consumption.

An open-source service monitoring system and time series database.

Intent signal monitoring CLI. Track LinkedIn engagers, keyword posters, job changers, funding events. JSON output for data pipelines.

Free real-time DEX data via SSE streaming across 34 blockchains. 30M+ pools, 27M+ tokens, ~1 second price updates. No API key, no rate limits. Docs

Event data simulator. Generates a stream of pseudo-random events from a set of users, designed to simulate web traffic.

Data generation platform for producing synthetic event streams with complex correlations.

Remote MCP server for real-time financial data, 3.2M+ news articles, ML options pricing, and news bias analysis. Free, no API key. MCP

Real-time data is available including comments, submissions and links posted to reddit.

Real-time X (Twitter) data API providing tweets, profiles, search, communities and engagement metrics. Up to 50x cheaper than the official X API with 20 req/sec rate limit, JSON output.

The Streaming APIs give developers low latency access to Twitter's global stream of Tweet data.

Open-source and free relational database schema discovery and comprehension tool. Documents and diagrams relational database schemas from your Java programs, build tools and the command line. Find database design issues with lint, and write scripts against the database. Includes an MCP Server for use by AI agents.

The AI native file format. Trust scores, source provenance, and compliance metadata that embed into 20+ formats (DOCX, PDF, images, code). EXIF for AI.

Apache Avro™ is a data serialization system.

The smallest, fastest columnar storage for Hadoop workloads.

A columnar storage format available to any project in the Hadoop ecosystem, regardless of the choice of data processing framework, data model or programming language.

The Apache Thrift software framework, for scalable cross-language services development.

A fast and efficient object graph serialization framework for Java.

Specialized JSONL log compressor with block-level timestamp indexing and DuckDB integration. Achieves ~9% compression ratio (better than gzip) with time-range random access queries.

A parallel implementation of gzip for modern multi-processor, multi-core machines.

Protocol Buffers - Google's data interchange format.

A flat file consisting of binary key/value pairs. It is extensively used in MapReduce as input/output formats.

A fast compressor/decompressor. Used with Parquet.

A unified programming model that implements both batch and streaming data processing jobs that run on many execution engines.

A streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations over data streams.

An open source framework for managing storage for real time processing, one of the most interesting feature is the Upsert.

An easy to use, powerful, and reliable system to process and distribute data.

A distributed stream processing framework.

A free and open source distributed realtime computation system.

A data-processing toolkit for python 3.5+.

An open source ETL framework to build fresh index for AI.

The streaming database built for IoT data storage and real-time processing.

An edge lightweight IoT data analytics/streaming software implemented by Golang, and it can be run at all kinds of resource-constrained edge devices.

Performant open-source Python ETL framework with Rust runtime, supporting 300+ data sources.

The Streaming SQL Database.

Forever scalable event processing & in-memory durable K/V store as a library with asyncio & static typing.

Makes it easy to build scalable fault-tolerant streaming applications.

Streaming and tasks execution between Spring Boot apps.

A framework for building real-time streaming data processing applications that supports a wide range of ingestion sources.

An ACID-compliant RDBMS which uses a shared nothing architecture.

- An API gateway built for event-driven architectures and streaming that supports standard protocols such as HTTP, SSE, gRPC, MQTT, and the native Kafka protocol.

Open-source agentic data quality framework with LLM-powered diagnosis, root-cause analysis, SQL auto-fix proposals, and 31 rule types — DuckDB, Postgres, BigQuery, Databricks, Athena, Snowflake.

Decorator-first DataFrame contracts/validation (columns/dtypes/constraints) at function boundaries. Supports Pandas/Polars/PyArrow/Modin.

Interview practice with SQL query execution, Python, and data modeling exercises.

Open Source Data Observability for end-to-end Data Journey Observability, data profiling, anomaly detection, and auto-created data quality validation tests.

Real-time data quality firewall for pipelines and APIs. Screens rows in milliseconds for schema drift, null spikes, type mismatches, and data anomalies with PASS / WARN / BLOCK decisions.

An open-source data quality platform for the whole data platform lifecycle from profiling new data sources to applying full automation of data quality monitoring.

JSON/XML validation and API contract monitoring tool for debugging and testing structured data.

A data catalog tool that integrates into your CI system exposing downstream impact testing of data changes. These tests prevent data changes which might break data pipelines or BI dashboards from making it to production.

Open Source data validation framework to manage data quality. Users can define and document “expectations” rules about how data should look and behave.

A vendor-neutral, declarative data quality engine. Define checks in YAML, run anywhere. Includes 16 built-in check types, SQL batch optimizer, anomaly detection, and data contracts.

Free online SQL playground for MySQL, PostgreSQL, and SQL Server. Create database structures, run queries, and share results instantly.

Zero-config data quality CLI. Profiles every table on first run, then auto-detects anomalies (volume drops, schema drift, freshness misses, distribution shifts) on subsequent runs. No YAML, no rules to write. Works with Postgres, BigQuery, Snowflake, and dbt.

A Snowflake-compatible emulator for local development and testing.

Write, run, and test PySpark code on Spark Playground's online compiler. Access real-world sample datasets & solve interview questions to enhance your PySpark skills for data engineering roles.

A system to programmatically author, schedule, and monitor data pipelines.

A batch workflow job scheduler created at LinkedIn to run Hadoop jobs. Azkaban resolves the ordering through job dependencies and provides an easy-to-use web user interface to maintain and track your workflows.

Governed, multi-tenant MCP access to your customers' data. Turn your warehouse, dbt, or semantic layer into a secure, per-customer MCP for AI agents.

End-to-end data pipeline tool that combines ingestion, transformation (SQL + Python), and data quality in a single CLI. Connects to BigQuery, Snowflake, PostgreSQL, Redshift, and more. Includes VS Code extension with live previews.

Java based application development platform.

A reverse-ETL tool that let you sync data from your cloud data warehouse to SaaS applications like Salesforce, Marketo, HubSpot, Zendesk, etc. No engineering favors required—just SQL.

An application cron-like system. Used w/Luigi. Deprecated.

An open-source Python library for building data applications.

Open-source platform for data preparation, synthetic data generation, and AI/data pipelines. Includes reusable skills for automating workflow steps across data and AI tasks.

An open-source framework and web based IDE to manage datasets and their dependencies. SQLX extends your existing SQL warehouse dialect to add features that support dependency management, testing, documentation and more.

A command line tool that enables data analysts and engineers to transform data in their warehouses more effectively.

A lightweight Python library for building execution pipelines with retry, parallel execution, cron scheduling, and async support.

A lightweight library to define data transformations as a directed-acyclic graph (DAG). If you like dbt for SQL transforms, you will like Hamilton for Python processing.

A framework that makes it easy to build robust and scalable data pipelines by providing uniform project templates, data abstraction, configuration and pipeline assembly.

Scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code.

A Python module that helps you build complex pipelines of batch jobs.

Open-source data pipeline tool for transforming and integrating data.

The open-source reverse ETL, data activation platform for modern data teams.

Self-hosted gateway for safe, auditable queries for agents across approved data sources.

A workflow scheduler system to manage Apache Hadoop jobs.

Open-source semantic sidecar that compiles YAML-defined dimensions, measures, and metrics into optimized SQL across 8 engines (BigQuery, ClickHouse, Databricks, Dremio, DuckDB, MySQL, PostgreSQL, Snowflake). Unified REST, MCP, and Postgres wire protocol; one model powers AI agents, analytics, DQ rules, and KPIs.

An open source framework that allows you to enforce agreements on how data should be accessed, used, and transformed, regardless of the data platform (Snowflake, BigQuery, DataBricks, etc.)

DAG based workflow manager. Job flows are defined programmatically in Python. Support output passing between jobs.

An orchestration and observability platform. With it, developers can rapidly build and scale resilient code, and triage disruptions effortlessly.

A warehouse-first Customer Data Platform that enables you to collect data from every application, website and SaaS platform, and then activate it in your warehouse and business tools.

An open-source data transformation framework for managing, testing, and deploying SQL and Python-based data pipelines with version control, environment isolation, and automatic dependency resolution.

Create automated workflows and logic using API's for your notification service. Add templates, batching, preferences, inapp inbox with workflows to trigger notifications directly from your data warehouse.