Optimizing Couchbase N1QL Queries with Composite Global Secondary Indexes
When N1QL queries turn full-table scans on growing datasets, a strategically composite GSI can restore sub-millisecond latency without application changes.
Loading…
ReadMeFeed / Community knowledge
Couchbase
Real questions. Useful conversations. Find the people who know your stack.
Couchbase
Databases & messaging · #couchbase
Architecting Couchbase XDCR for Regional Read Scaling and Disaster Recovery
Learn how to design a Couchbase XDCR architecture for disaster recovery and regional read scaling, focusing on minimal cluster footprints, trust boundaries, and lag monitoring.
Couchbase FTS and N1QL: A Practical Pattern for Search-First Apps
Use Couchbase Full-Text Search to shortlist document IDs by relevance, then fetch full documents with N1QL. A practical pattern for search-first applications that avoids expensive bucket scans.
Using Couchbase Full‑Text Search: Create, Query, and Avoid Common Pitfalls
Learn how to set up a Couchbase Full‑Text Search (FTS) index, run queries from Java, and what to watch out for—analyzers, index health, and numeric fields.
Choosing Between GSI and N1QL Views in Couchbase for Query Performance
Guide to deciding between Couchbase GSI and N1QL Views, with a comparison table, trade‑off analysis, and step‑by‑step GSI creation and validation.
Using Couchbase Sub‑Document API to Update JSON Fields Efficiently
Learn how Couchbase’s Sub‑Document API lets you increment counters and append array items without fetching the whole document, saving bandwidth and latency.
Couchbase Sub-Document API: Cutting Payload and CAS Contention on Hot JSON Fields
Full-document get and replace operations waste bandwidth and amplify CAS contention when only a few fields change. Here is how lookupIn and mutateIn let you read and write individual JSON paths, with a user-profile example and the trade-offs to check before migrating.
jsonOptimizing Couchbase Query Performance with Global Secondary Indexes (GSI)
Learn how to eliminate slow primary scans in Couchbase by implementing Global Secondary Indexes (GSI), including composite and covering indexes to optimize query latency.
Diagnosing & Fixing High N1QL Latency Caused by Missing or Inefficient Indexes in Couchbase
When N1QL queries stall, the first culprit is often an absent or poorly defined index. This guide walks through spotting full scans, interpreting query plans, and applying targeted index changes to bring latency back under control.