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Elasticsearch Data Streams simplify time-series data management with one name for many indices.

Elasticsearch offers Data Streams for simplicity and Time-Based Indices for control in managing time-series data.

Elasticsearch offers two pagination methods: from & size for shallow pages and search_after for deep pages.

Elasticsearch mapping defines how fields are indexed and searched, with dynamic and explicit options.

The number of Elasticsearch nodes depends on storage, workload, and performance needs.

Elasticsearch uses shards for data distribution and replicas for redundancy.

Elasticsearch CCR allows real-time data replication for faster disaster recovery.

Choose Elasticsearch for complex text searches, but use databases for structured queries.

Elasticsearch distributes search queries across shards to find and retrieve results quickly.

A document in Elasticsearch isn't searchable right after it's saved due to the refresh process.

Elasticsearch index templates automatically apply settings to new indices based on patterns.

Elasticsearch ILM automates index management to reduce storage costs and meet data needs.

Elasticsearch aliases allow zero-downtime switching between indices for applications.

You can update Elasticsearch indices without downtime using alias switching.

Filters check conditions without affecting relevance, while queries do.

Elasticsearch ILM automates data management through defined lifecycle phases.