# dynamic-updates

> Browse 5 items tagged with dynamic-updates.

## 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.
- [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.
- [FreshDiskANN](https://vectordb.ever.works/items/freshdiskann) — Fast and accurate graph-based ANN index for streaming similarity search, enabling real-time updates on billion-point indexes using a single machine with real-time freshness.
- [SPFresh](https://vectordb.ever.works/items/spfresh) — Incremental in-place update system for billion-scale vector search from Microsoft Research. Maintains 2.41x lower P99.9 latency than baselines while supporting efficient vector updates with minimal resource overhead.
- [M-tree](https://vectordb.ever.works/items/m-tree) — M-tree is a dynamic index structure for organizing and searching large data sets in metric spaces, enabling efficient nearest neighbor queries and dynamic updates, which are important features for vector databases handling high-dimensional vectors.

---

_Canonical page: https://vectordb.ever.works/tags/dynamic-updates_