Weaviate on Stackoverflow badge Weaviate issues on Github badge Weaviate total Docker pulls badge

💡 You are looking at older or release candidate documentation. The current Weaviate version is v1.15.2


Scalability is one of Weaviate’s core features. The following roadmap aims to give you an understanding of where we are taking Weaviate from a scalability and implementation perspective.

Video: introduction to the Weaviate architecture

Complete Roadmap

HNSW Perfomance Boosts
status: done in v1.4.0
Hardware-acceleration and efficiency improvements reduce the time it takes to perform a vector search or index into the vector index by up to 50%.
LSM Tree Migration
status: done in v1.5.0
The way that objects and the inverted index are stored within Weaviate are migrated from a B+Tree-based approach to an LSM-Tree approach. This can speed up import times up to 50%. Also addresses import times degrading over time.
Multi-shard indices
status: in progress (follow on GitHub)
A monolithic index (one index per class) can be broken up into smaller independent shards. This allows utilizing resources on large (single) machines better and allows for tweaking storage settings for specific large-scale cases.
Horizontal Scalability without replication
An index, comprised of many shards, can be distributed among multiple nodes. A search will touch multiple shards on multiple nodes and combine the results. Major benefit: If a use case does not fit on a single node, you can use *n* nodes to achieve *n* times the use case size. At this point every node in the cluster is still a potential single point of failure.
Replication shards distributed across nodes
A node can contain shards which are already present on other nodes as well. This means if a node goes down, another node can take up the load without the loss of availability or data. Note that the design plans for a leaderless replication, so there is no distinction between primary and secondary shards. Removes all single point of failures.
Dynamic scaling
Instead of starting out with a cluster with *n* nodes, the cluster size can be increased or shrank at runtime. Weaviate automatically distributes the existing shards accordingly.

Download the Roadmap

You can download the complete roadmap (as image) here too

More Resources

If you can’t find the answer to your question here, please look at the:

  1. Frequently Asked Questions. Or,
  2. Knowledge base of old issues. Or,
  3. For questions: Stackoverflow. Or,
  4. For issues: Github. Or,
  5. Ask your question in the Slack channel: Slack.