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.
Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
Python Streaming DataFrames for Kafka
:truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
High performance Rust stream processing engine seamlessly integrates AI capabilities, providing powerful real-time data processing and intelligent analysis.
Download, unpack from a ZIP/TAR/GZ/BZ2 archive, parse, correct, convert units and import Google Spreadsheets, XLS, ODS, XML, CSV, HTML, etc. into your ActiveRecord models. Uses RemoteTable gem internally.
📜 A CLI toolkit for extracting and working with your digital history
Blockchain Indexing Engine
An Apache Spark framework for easy data processing, extraction as well as derivation for web archives and archival collections, developed at Internet Archive.
Please note that the warc-indexer tool & code is now supported by NetArchiveSuite. The 'warc-indexer' directory and code that exists in this repo is now only for reference. For support and issues of 'warc-indexer', please communicate with NetArchiveSuite.
Insert incoming MQTT values into InfluxDB. Follows mqtt-smarthome architecture.
Internet Archive's Sparkling Data Processing Library