api: YAML JSON TOON Database
version: 1.0.0
format: toon
dataset:
  id: 2365
  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[2]: You are picking a category of database for a new system.,You need quick examples of each category.
  caveats[2]: "Categories overlap and products borrow from each other; PostgreSQL stores JSON and supports vectors, for example.","Examples are illustrative, not rankings or recommendations."
  related[4]: nosql-databases-overview,acid-vs-base,sql-query-types,cap-theorem
  entry_count: 11
  fields[4]{section,field,type,example}:
    databases,type,string,Relational
    databases,examples,string,"PostgreSQL, MySQL, SQLite"
    databases,model,string,Tables with rows and columns
    databases,best_for,string,"Structured data, ACID transactions, complex que…"
  category: Database Types
  category_slug: database-types
  tags: "database,sql,nosql,comparison"
  view_count: 58
  created_at: 1777673262
  updated_at: 1777673262
data:
  databases[11]{type,examples,model,best_for}:
    Relational,"PostgreSQL, MySQL, SQLite",Tables with rows and columns,"Structured data, ACID transactions, complex queries"
    Document,"MongoDB, CouchDB",JSON-like documents,"Flexible schemas, rapid development, hierarchical data"
    Key-Value,"Redis, DynamoDB",Key-value pairs,"Caching, session storage, high throughput"
    Column-Family,"Cassandra, HBase",Columns grouped in families,"Time-series, write-heavy workloads, big data"
    Graph,"Neo4j, ArangoDB",Nodes and edges,"Relationship-heavy data, social networks, recommendations"
    Vector,"Pinecone, Weaviate, pgvector",High-dimensional vectors,"Semantic search, similarity matching, RAG"
    Time-Series,"InfluxDB, TimescaleDB, Prometheus",Timestamped measurements optimized for append and range queries,"Metrics, IoT sensor data, monitoring and financial ticks"
    Search Engine,"Elasticsearch, OpenSearch, Apache Solr",Inverted indexes over documents with relevance scoring,"Full-text search, log analytics, faceted navigation"
    Distributed SQL (NewSQL),"CockroachDB, TiDB, Google Spanner",Relational tables with SQL and distributed transactions,Horizontally scaled applications that need SQL and strong consistency
    In-Memory,"Redis, Memcached, SAP HANA",Data held primarily in RAM,"Caching, session stores, leaderboards, low-latency analytics"
    Multi-Model,"ArangoDB, Azure Cosmos DB, SurrealDB",Several data models behind one engine,"Applications mixing document, graph and key-value access"