Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
- batch-processing
- kafka
- pathway
- python
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Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
Apache Spark - A unified analytics engine for large-scale data processing
All-in-one IoT Platform - Device management, data collection, processing and visualization.
An orchestration platform for the development, production, and observation of data assets.
The Open Context Layer for Data and AI , OpenMetadata is the open platform for building trusted data context and business semantics for humans, AI assistants, and agents.
dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
The leader in Customer Data Infrastructure
🔩 Like builtins, but boltons. 250+ constructs, recipes, and snippets which extend (and rely on nothing but) the Python standard library. Nothing like Michael Bolton.
🦀 event stream processing for developers to collect and transform data in motion to power responsive data intensive applications.
A network event stream processing system, in Clojure.
Blazing-fast, Neuro-symbolic Data-Wrangling toolkit
High-performance time-series aggregation for PostgreSQL
The fastest unified streaming SQL Engine in a single C++ binary. ⚡ Millisecond latency. 100+ GB/s throughput. Continuously compute stateful context from streams, logs, metrics, events, and CDC.
:elephant: Elasticsearch real-time search and analytics natively integrated with Hadoop
Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows.
Lightweight data stream processing engine for IoT edge
👜 Tiny and fast reactive/iterable programming library
Nessie: Transactional Catalog for Data Lakes with Git-like semantics
visual data prep powered by python
📈 Collect customer event data from your apps. (Note that this project only includes the API collector, not the visualization platform)
Apache StreamPipes - A self-service (Industrial) IoT toolbox to enable non-technical users to connect, analyze and explore IoT data streams.