Multi-Dimensional Scaling

Couchbase Multi-Dimensional Scaling (MDS) improves performance and lowers costs by scaling services independently and avoiding the wasted resources of all-in-one designs.

whitepaper

Couchbase Under the Hood

Storage and key/value access for JSON documents.

SQL++ query engine can be used with Data and Index services.

Primary and secondary indexes on data.

Full-text, geospatial, and vector search for AI.

Real-time workload-isolated analytics and SQL++.

Real-time logic to respond to mutations/times.

Speed without interference

Dedicated query nodes ensure fast processing without slowing down reads or writes. By isolating query operations, you avoid CPU contention with other services, and you can scale query nodes without rebalancing data. This makes queries consistently fast, even under heavy loads.

High-speed lookup, zero bottlenecks

Index services benefit from SSDs and operate best when isolated. This keeps writes fast since disk I/O isn’t shared with other services. You can scale indexing independently and create as many indexes as needed without affecting data distribution or write performance.

Consistent reads and writes at scale

When data nodes are isolated from query and index workloads, reads and writes stay fast and predictable. You don’t have to rebalance queries or indexes to scale the data layer, and you can prioritize memory while using more modest CPU and disk resources.

What customers are saying

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