Observed Signal · May 26, 2026 · Technical Release · Source: DEV Community · Impact: 2/5 · Sentiment: Neutral
Guide to Database Types and Use Cases
A technical guide published on May 26, 2026 that explains the main database categories, how they work, and when to use them. The article summarizes ten database types — relational (SQL), NoSQL (document, key-value, wide-column, graph), NewSQL, vector, time-series, search, in-memory, object-oriented, cloud-native/serverless, and multi-model — and gives vendor examples and common use cases for each. It also covers foundational concepts (ACID vs BASE, the CAP theorem, sharding vs replication) and clarifies technologies often mistaken for databases (Debezium, Apache Kafka, Elasticsearch). The piece emphasizes polyglot persistence: modern systems commonly combine multiple database types to meet different requirements.
Database selection and architecture are foundational to application scalability, data pipelines, AI/ML (vector DBs/embeddings) and real‑time systems; the guide consolidates practical comparisons that inform infrastructure decisions across tech stacks including AdTech.
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Key Takeaways & Evidence Grounding
- Published on 2026-05-26.
- Defines and compares 10 database types, including Relational, NoSQL (document, key-value, wide-column, graph), NewSQL, vector, time-series, search, in‑memory, object‑oriented, cloud‑native/serverless, and multi‑model.
- Provides concrete vendor examples (e.g., MySQL, PostgreSQL, MongoDB, DynamoDB, Cassandra, Neo4j, CockroachDB, Spanner, Pinecone, InfluxDB, Elasticsearch).
- Explains core principles: ACID vs BASE, the CAP theorem, sharding vs replication.
- Clarifies that tools like Debezium and Apache Kafka are change‑data/streaming tools, not primary databases.
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