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Discover top open-source software, updated regularly with real-world adoption signals.
Discover top open-source software, updated regularly with real-world adoption signals.
Unified Python framework for real‑time, batch, and LLM pipelines
Pathway lets Python developers build scalable batch and streaming pipelines, add AI/LLM steps, and deploy via Docker or Kubernetes, leveraging a high‑performance Rust engine.
When teams consider Pathway, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Real‑time ETL from Kafka to PostgreSQL
Continuously ingest Kafka events, transform, and upsert into PostgreSQL with at‑least‑once guarantees.
Event‑driven alerting pipeline
Detect threshold breaches in streaming data and push alerts to Slack or email in seconds.
Adaptive RAG with live document updates
Index new documents on the fly and serve up‑to‑date answers via LLM without re‑training.
Batch CSV processing with incremental updates
Process large CSV dumps, then apply incremental changes as new rows arrive, keeping results current.
Run `pip install -U pathway` on Python 3.10+; Docker images are also provided.
Official binaries run on macOS and Linux; Windows users can run Pathway inside a virtual machine.
The free version offers at‑least‑once processing; the enterprise edition adds exactly‑once guarantees.
Yes, you can build a custom Python connector or use the Airbyte connector to access over 300 sources.
Package your pipeline in the provided Docker image and deploy multiple replicas; the Rust engine handles multithreading and distributed execution.
Project at a glance
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