Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)

Upserts, Deletes And Incremental Processing on Big Data.

StarRocks, a Linux Foundation project, is a next-generation sub-second MPP OLAP database for full analytics scenarios, including multi-dimensional analytics, real-time analytics, and ad-hoc queries. InfoWorld’s 2023 BOSSIE Award for best open source software.

Dinky is a real-time data development platform based on Apache Flink, enabling agile data development, deployment and operation.

Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.

Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai

LakeSoul is an end-to-end, realtime and cloud native Lakehouse framework with fast data ingestion, concurrent update and incremental data analytics on cloud storages for both BI and AI applications.

lakeFS - Data version control for your data lake | Git for data

Apache Amoro (incubating) is a Lakehouse management system built on open data lake formats.

汇总Apache Hudi相关资料

The LeoFS Storage System

World's most powerful data catalog service with providing a high-performance, geo-distributed and federated metadata lake.

Apache Spark Course Material

Apache Doris Website

A free to use dbt package for creating and loading Data Vault 2.0 compliant Data Warehouses (powered by dbt, an open source data engineering tool, registered trademark of dbt Labs)

Scalable identity resolution, entity resolution, data mastering and deduplication using ML

Postgres for Search and Analytics

Apache Spark 3 - Structured Streaming Course Material

This repository will help you to learn about databricks concept with the help of examples. It will include all the important topics which we need in our real life experience as a data engineer. We will be using pyspark & sparksql for the development. At the end of the course we also cover few case studies.

Real-time Data Warehouse with Apache Flink & Apache Kafka & Apache Hudi