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BaseKV
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Docs & Quickstart

BaseKV supports Redis and Memcached client protocols, a DynamoDB-style API for simple item get/put workflows, and a RedisGraph-style command subset for property graph use cases. Start by creating a database, then point your client at the BaseKV endpoint. You can run the same workflow from a human dashboard today and move toward machine-managed automation.

Quickstart

  1. Create a database in the dashboard.
  2. Choose your access path: Redis, Memcached, DynamoDB-style, or Redis graph commands.
  3. Copy the endpoint details for that protocol.
  4. Update your client connection settings.
  5. Write a test key to confirm connectivity.

Graph Compatibility Subset

BaseKV exposes RedisGraph-style commands for teams that model data as nodes and edges. The mental model is close to Neo4j (property graph + Cypher-like queries), but the implementation is a compatibility subset and not full Neo4j or full RedisGraph parity.

Supported commands:

GRAPH.QUERYGRAPH.RO_QUERYGRAPH.EXPLAINGRAPH.PROFILEGRAPH.CONFIGGRAPH.LISTGRAPH.DELETE
  • Cypher subset includes CREATE, MERGE, MATCH, WHERE, SET, DELETE, RETURN, LIMIT, and basic relationship patterns.
  • Read-only flows can use GRAPH.RO_QUERY, which rejects write statements.
  • Graph keys integrate with Redis keyspace operations like TYPE, EXISTS, DEL, KEYS, and SCAN.
Neo4j performance positioning (working estimate)

For deep traversals (3+ hops), current BaseKV graph execution is typically slower than Neo4j because traversals resolve adjacency through BoltDB index lookups rather than index-free pointer jumps.

  • Small graphs (<10k nodes): often negligible user-visible differences.
  • Medium graphs (10k-1M nodes): commonly around 5x-15x slower for traversal-heavy patterns.
  • Deep traversal workloads: practical range is often 10x-50x slower today; at very large graph sizes this can exceed 50x.

Treat these numbers as planning guidance, not formal benchmarks. Always benchmark your own query mix before production commitments.

Graph compatibility overview →

For Agents

If you are evaluating BaseKV for autonomous workflows, start with the agent quickstart and security model before scaling automation. Use the lifecycle API guide for task-by-task automation and the MCP status page for integration direction.

Machine-readable discovery endpoints are available for integration bootstrap and tooling.

Agent quickstart →Agent security model →Lifecycle API guide →MCP status →OpenAPI spec →OAuth metadata →Agent card →

Switching notes

For Redis users, swap your connection string and keep your client library. For Memcached, you can often keep the same client with a new endpoint. For DynamoDB-style integrations, BaseKV targets simple item get/put workflows rather than full DynamoDB feature parity. For graph workloads, BaseKV offers RedisGraph-style command compatibility with a practical subset and should be validated query-by-query. BaseKV focuses on compatibility you can validate, not opaque migrations.

See the compatibility page for a practical overview of what each integration is intended for.

Compatibility overview →