AlloyDB ScaNN Dives Deep: Vector Search Hits 10 Billion
Quick answer
AlloyDB's ScaNN index now scales to 10 billion vectors with a new four-level tree, hitting 51ms p95 latency and 95% recall. Dive into the details.
When your vector database starts sweating over a billion vectors, you know it’s time to paddle faster. Google’s AlloyDB just did exactly that, scaling its ScaNN index to a whopping 10 billion vectors. That’s not just a splash—it’s a whole new swimming hole for enterprise AI.
AlloyDB, the fully managed PostgreSQL-compatible service, has been a favorite among capybaras who like their databases robust and their queries quick. Now, with a new four-level tree architecture (currently in preview), it’s tackling the kind of scale that would make a caiman think twice.
The 10 Billion Vector Wall
Scaling to 10 billion vectors isn’t just about adding more memory—it’s about not drowning in compute. The old two- and three-level tree structures hit a wall: more vectors meant more compute intensity and memory constraints that could sink the whole operation.
- Compute intensity: Bigger trees require more operations for both building and querying.
- Memory constraints: Sampling 10 billion vectors can easily exceed available memory.
Four-Level Tree: The New Deep End
The solution? A four-level tree that uses hierarchical partitioning to narrow down search space exponentially. Instead of scanning a flat swamp, the search path gets funneled through increasingly refined layers, cutting complexity from O(N1/2) down to O(N1/4).
This isn’t just about adding a level—it’s about smart engineering. The team integrated enhancements like Top-K branch, SOAR, centroid adjustment, and balanced tree shape to keep recall high and build efficient.
Memory Efficiency: The Secret Sauce
To fit 10 billion vectors without blowing up memory, AlloyDB uses a balanced tree shape that reduces sampling sizes while keeping partitions high-fidelity. When memory gets tight, it generates a condensed sampling set that balances performance and accuracy.
Performance That Makes Waves
In internal tests, AlloyDB ScaNN with the four-level tree delivered:
- Support for over 10 billion vectors
- p95 latency of ≤51 ms
- 95% recall at that scale
That’s the kind of speed that lets you build agentic AI without waiting for the current to catch up.
Dive In Today
Ready to take the plunge? The four-level tree is available in preview. You can get started with the quickstart guide or check out the official ScaNN documentation. New users can also explore AlloyDB with a 30-day free trial.
While you’re at it, if you’re comparing database options, our Google Cloud review and Supabase review might help you decide which pond to swim in. And for vector search at scale, AlloyDB is clearly making a big splash.
Original announcement published on Google Cloud.