Weaviate’s Architecture from above

The above gives a 30,000 feet view of Weaviate’s architecture. On these pages you can learn more about the individual sections:

• Learn about Storage inside a shard
  • How Weaviate stores data
  • How Weaviate makes writes durable
  • How an inverted index, a vector index and an object store interact with each other
• Ways to scale Weaviate horizontally
  • Different motivations to scale
  • Sharding vs. Replication
  • Configuring a cluster
  • Consistency
• How to plan resources
  • The roles of CPU, Memory and GPUs
  • How to size a cluster correctly
  • Speeding up specific processes
  • Preventing bottlenecks
• The module system
  • How Weaviate can be extended through modules
  • The various roles of modules (vectorizers, etc.)
  • Creating your own modules or adapting existing modules to your needs
• Filtered Vector Search
  • Combine vector search with filters
  • Learn how combining an HNSW with an inverted index leads to high-recall, high-speed filtered queries
• User-facing interfaces
  • Design philosophy behind user-facing APIs
  • Role of the REST and GraphQL APIs
• Roadmap
  • Learn about features currently under development
  • What will Weaviate be like in the future from an architectural perspective?

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.