# streaming

> Browse 5 items tagged with streaming.

## Items

- [In-Place Updates of Graph Index](https://vectordb.ever.works/items/in-place-updates-graph-index) — A 2026 research paper on streaming approximate nearest neighbor search with in-place graph index updates. The approach enables real-time index modifications without expensive rebuilds, crucial for dynamic datasets.
- [Pathway](https://vectordb.ever.works/items/pathway-realtime-vector-indexing) — A Python ETL framework for stream processing and real-time analytics with built-in real-time vector indexing. Pathway automatically detects document changes and re-indexes in real-time, ensuring AI applications always use the latest information rather than stale data.
- [Updatable Balanced Index for Stable Streaming](https://vectordb.ever.works/items/updatable-balanced-index-streaming) — Research on maintaining balanced, high-quality graph indexes while streaming data arrives continuously. Addresses the challenge of index degradation over time with incremental updates.
- [Streaming Vector Indexing](https://vectordb.ever.works/items/streaming-vector-indexing) — Real-time indexing of vectors as they arrive in a stream, enabling immediate searchability without batch processing delays. Critical for applications requiring up-to-the-second freshness like social media, news, or real-time recommendations.
- [Pathway](https://vectordb.ever.works/items/pathway) — Python ETL framework for stream processing and real-time analytics with built-in vector search capabilities. Features real-time document synchronization, in-memory vector index, and adaptive RAG technology for always-current AI applications.

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