ReadMeFeed / Community knowledge
Real questions. Useful conversations. Find the people who know your stack.
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.
Learn how to eliminate slow primary scans in Couchbase by implementing Global Secondary Indexes (GSI), including composite and covering indexes to optimize query latency.
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.
Couchbase scopes and collections offer logical isolation inside a bucket, but memory, flush, and replicas stay bucket-wide. Learn how N1QL keyspaces, per-collection indexes, and RBAC paths work, and when to choose collections over separate buckets.
Learn how to add a Couchbase secondary index that turns expensive full‑bucket scans into fast index‑only lookups, with a concrete example, verification steps, and trade‑offs.
Deep OFFSET pages in Couchbase N1QL scan and skip rows, degrading as page depth grows. This guide shows how to build a covering composite index, encode a cursor from the last sort key and unique tiebreaker, and verify the plan with EXPLAIN.
Learn how to replace inefficient Primary Indexes in Couchbase with Global Secondary Indexes and Covering Indexes to eliminate data fetches and reduce query latency.
Prepared statements let Couchbase N1QL reuse a query plan instead of re-parsing every request. Here is the PREPARE/EXECUTE cycle, a reproducible example, and the stale-plan trade-off.
Couchbase 7.0 introduced Scopes and Collections, a three‑level hierarchy that lets you isolate tenants, indexes, and permissions inside a single bucket—no more bucket sprawl or giant type‑field indexes.
couchbase