A Comprehensive Overview of Nine Database Types and Polyglot Persistence Practices
This article provides an in‑depth survey of nine database categories—including relational, key‑value, columnar, document, graph, time‑series, and vector databases—detailing their architectures, advantages, disadvantages, best‑practice recommendations, typical use cases, and how they can be combined in polyglot persistence solutions.
In the digital era, data is a core asset and selecting the right database is crucial; this article surveys nine database categories—relational (MySQL), key‑value (Redis), column‑oriented (HBase, ClickHouse), document (MongoDB, ElasticSearch), graph (Neo4j), time‑series (Prometheus) and vector (Milvus)—detailing their architectures, strengths, weaknesses, best‑practice recommendations and typical application scenarios.
The article also presents the June 2024 DB‑Engines ranking, explains the concept of polyglot persistence, and illustrates real‑world deployment patterns such as MySQL + Redis, HBase + ElasticSearch, and HBase + Redis + ElasticSearch for high‑volume order systems.
Finally, it offers guidance on choosing databases based on workload, scalability, consistency, cost and ecosystem considerations, and provides references to official documentation and further reading.
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