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Developer tools · #elasticsearch
When deciding how to implement search for a Couchbase‑backed application, you can either use Couchbase Server’s built‑in Full‑Text Search or hook up an external Elasticsearch cluster. This guide compares the two options, discusses trade‑offs, and walks through a sample validation test.
When an Elasticsearch cluster turns Yellow or Red, unassigned shards are usually the culprit. This guide walks through the diagnostic steps, root causes, and targeted fixes—covering shard counts, replica settings, and allocation rules—to bring your cluster back to Green.
Searchable Snapshots let you query cold Elasticsearch indices straight from S3 or other object storage without restoring them to local disk. Here's how mounting works, a worked example, and the read-only and latency trade-offs to plan for.
A decision guide for choosing between Neo4j's native Lucene-based indexes and Elasticsearch integration based on latency, consistency, and scale.
A decision guide for selecting the search engine backend in Shopware 6.5+: compare Elasticsearch, OpenSearch, and MySQL fulltext with constraints, trade-offs, and a concrete OpenSearch validation workflow.
A decision guide for picking Elasticsearch's keyword vs text field types, with a comparison table, trade‑off analysis, and a ready‑to‑run multi‑field mapping plus validation queries.
Logstash's Dead Letter Queue persists events that outputs reject so you can reprocess them later. Here's how to enable it, drain it safely, and avoid the disk-space traps.
A concise decision guide that compares PostgreSQL’s built‑in full‑text search with ElasticSearch, outlines constraints, trade‑offs, and shows a concrete implementation with verification steps.
Learn how Elasticsearch ILM automates index rollover and deletion based on size or age, reducing manual cleanup and preventing disk‑related cluster issues.
couchbase
shopware
logstash