Database / Weaviate Vector database Interview questions
What is sharding in Weaviate?
Sharding splits a collection's data horizontally across multiple nodes, with each shard holding a subset of the collection's objects, letting a single collection scale beyond what any one node's storage and compute capacity could handle alone.
client.collections.create( name="Products", sharding_config=Configure.sharding(desired_count=4) )
Sharding and replication solve different problems and are typically used together: sharding lets total data volume and write throughput scale by spreading data across more nodes, while replication lets any given shard survive node failure and serve more concurrent read traffic. A search query against a sharded collection fans out to every relevant shard and merges the results, conceptually similar to how other distributed vector databases handle horizontal scaling.
Sharding in Weaviate is used to:
Sharding and replication are typically used:
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