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Databases Intermediate

What is Time-Series Database?

A database optimized for storing and querying timestamped data points like metrics, sensor readings, and event logs.

Time-series databases are specialized for data that arrives sequentially over time. They optimize for high write throughput, time-range queries, and downsampling/aggregation. Examples include TimescaleDB (PostgreSQL extension), InfluxDB, Prometheus (for metrics), and QuestDB. Key features include automatic partitioning by time, built-in aggregation functions (moving averages, percentiles), data retention policies, and compression. They are essential for IoT, monitoring, financial data, and any application tracking changes over time.

Related Terms

Schema
The structure definition of a database including tables, columns, data types, relationships, indexes, and constraints.
NoSQL
A category of databases that store data in non-tabular formats, optimized for specific data models and access patterns.
Row-Level Security (RLS)
A database feature that restricts which rows a user can access in a table based on security policies.
Data Warehouse
A centralized repository optimized for analytical queries that integrates data from multiple operational sources.
Elastic Search
A distributed search and analytics engine built on Apache Lucene, optimized for full-text search and log analysis.
Stored Procedure
A precompiled collection of SQL statements stored in the database that can be executed as a single unit.
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