Open Source Data Warehousing & Processing Software
Data Warehousing & Processing software manages the collection, storage, and analysis of large volumes of event streams and sensor readings. These tools enable high-throughput SQL queries and real-time analytics for industrial assets and web applications. This type of software serves data engineers and analysts who need to process massive datasets without relying on external cloud vendors. Self-hosting these apps ensures that sensitive event logs and telemetry data remain on private infrastructure. You can scale your ingestion pipelines and query performance according to your specific hardware capabilities.
This page lists 7 open source tools in the Data Warehousing & Processing category. The most popular are ThingsBoard, Apache Druid and Databend. Most use the Apache-2.0 or MIT license, and 7 offer an official Docker image.
ThingsBoard
Collect, process, visualize, and manage data from Internet of Things devices and industrial assets.
Apache Druid
A high performance real-time analytics database designed for fast queries and high concurrency data ingestion.
Databend
An open-source cloud data warehouse for large-scale analytics, vector search, and full-text search using Rust.
Jitsu
Collect event data from websites and applications to stream into data warehouses and other external services.
RudderStack
Collect customer data from applications and websites to activate it in warehouses and business tools.
Timeplus Proton
Run high‑throughput SQL pipelines for streaming analytics and AI using a single C++ binary.
Trench
Track and query large volumes of events in real time using Apache Kafka and ClickHouse.
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