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Redis is a fast in-memory data store used for caching and low-latency applications.

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

Search engines collect, index, retrieve, and rank documents to provide relevant results.

The Cache-Aside Pattern speeds up data retrieval by using a cache to store frequently accessed data.

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

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

API pagination helps manage large datasets by breaking them into smaller parts.

Caching helps applications respond faster by serving data from memory instead of hitting the database.

An inverted index helps search engines quickly find documents containing specific terms.

The Bulkhead Pattern isolates resources to protect critical workloads from failures.

Elasticsearch uses distributed architecture to search data quickly across multiple servers.

Distributed caching spreads data across multiple servers for better performance and reliability.

Token Bucket allows burst traffic, while Leaky Bucket smooths out traffic flow.