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The choice between SQL and NoSQL databases depends on your application's specific needs.

Downsampling and aggregation reduce data volume while preserving essential trends.

Data warehouses help businesses analyze large amounts of data for better decision-making.

Time-series databases are designed to store and query time-stamped metrics efficiently.

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

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

Database bottlenecks slow down performance, but identifying them helps optimize and scale effectively.

Sharding splits databases into smaller parts to improve performance and scalability.

Time-based partitioning organizes time-series data into smaller, efficient segments for better querying.

CQRS separates how we change data from how we read data, improving scalability.

B-Trees help databases find data quickly without scanning every row.

Filters check conditions without affecting relevance, while queries do.

OLTP handles transactions while OLAP is for data analysis and reporting.

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

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

Choosing between a shared database and a database per service affects system design significantly.

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

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

Cache breakdowns can overwhelm databases, but request coalescing solves this issue.

Cache penetration occurs when requests for non-existent data overload the database.

Retention policies help manage how long data is kept in databases.

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

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

Connection pooling reuses database connections but can cause issues if misconfigured.

Scaling databases involves deciding whether to enhance read or write capabilities based on traffic patterns.

REST API design focuses on creating clean, efficient, and scalable web services.

Elasticsearch fuzzy search allows finding results even with typos in queries.