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Database per Service ensures each microservice owns its data, reducing dependencies.

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

HLD provides an overview of system architecture, while LLD details implementation specifics.

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

FAANG engineers use high-level design principles to create scalable systems.

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

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

Kafka Schema Evolution allows safe changes to message structures without breaking existing consumers.

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

Kafka uses retention to keep historical data and compaction to keep the latest state.

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

Consistency models determine what data reads in distributed systems can see.

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

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