api: YAML JSON TOON Database
version: 1.0.0
format: json
dataset:
  id: 10
  slug: database-comparison
  title: Database Systems Comparison
  description: "Comparison of database types: Relational, Document, Key-Value, Column-Family, Graph, and Vector databases with examples and best-fit use cases."
  summary: "The main families of database systems and what each is best for: relational, document, key-value, column-family, graph and vector, extended with time-series, search, distributed SQL, in-memory and multi-model systems. Each row gives the data model and example products."
  use_when:
    - You are picking a category of database for a new system.
    - You need quick examples of each category.
  caveats:
    - Categories overlap and products borrow from each other; PostgreSQL stores JSON and supports vectors, for example.
    - Examples are illustrative, not rankings or recommendations.
  related:
    - nosql-databases-overview
    - acid-vs-base
    - sql-query-types
    - cap-theorem
  category: Database Types
  category_slug: database-types
  tags: database,sql,nosql,comparison
  view_count: 0
  created_at: 1777673262
  updated_at: 1777673262
  entry_count: 11
  fields:
    - section: databases
      field: type
      type: string
      example: Relational
    - section: databases
      field: examples
      type: string
      example: PostgreSQL, MySQL, SQLite
    - section: databases
      field: model
      type: string
      example: Tables with rows and columns
    - section: databases
      field: best_for
      type: string
      example: Structured data, ACID transactions, complex que…
data:
  databases:
    - type: Relational
      examples: PostgreSQL, MySQL, SQLite
      model: Tables with rows and columns
      best_for: Structured data, ACID transactions, complex queries
    - type: Document
      examples: MongoDB, CouchDB
      model: JSON-like documents
      best_for: Flexible schemas, rapid development, hierarchical data
    - type: Key-Value
      examples: Redis, DynamoDB
      model: Key-value pairs
      best_for: Caching, session storage, high throughput
    - type: Column-Family
      examples: Cassandra, HBase
      model: Columns grouped in families
      best_for: Time-series, write-heavy workloads, big data
    - type: Graph
      examples: Neo4j, ArangoDB
      model: Nodes and edges
      best_for: Relationship-heavy data, social networks, recommendations
    - type: Vector
      examples: Pinecone, Weaviate, pgvector
      model: High-dimensional vectors
      best_for: Semantic search, similarity matching, RAG
    - type: Time-Series
      examples: InfluxDB, TimescaleDB, Prometheus
      model: Timestamped measurements optimized for append and range queries
      best_for: Metrics, IoT sensor data, monitoring and financial ticks
    - type: Search Engine
      examples: Elasticsearch, OpenSearch, Apache Solr
      model: Inverted indexes over documents with relevance scoring
      best_for: Full-text search, log analytics, faceted navigation
    - type: Distributed SQL (NewSQL)
      examples: CockroachDB, TiDB, Google Spanner
      model: Relational tables with SQL and distributed transactions
      best_for: Horizontally scaled applications that need SQL and strong consistency
    - type: In-Memory
      examples: Redis, Memcached, SAP HANA
      model: Data held primarily in RAM
      best_for: Caching, session stores, leaderboards, low-latency analytics
    - type: Multi-Model
      examples: ArangoDB, Azure Cosmos DB, SurrealDB
      model: Several data models behind one engine
      best_for: Applications mixing document, graph and key-value access