awesome-data-engineering

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.

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.

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

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.

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

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

The show about modern data infrastructure.

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.

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 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.

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.

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.