Popular databases.
This mindmap diagram provides a categorization of various popular databases (2024) split by their primary functionality:
1) Relational Databases: Traditional databases that store data in rows and columns, ensuring data integrity and supporting complex queries through SQL. Main RDBMS’s include MySQL, PostgreSQL, Oracle Database, and Microsoft SQL Server.
2) NoSQL Databases: Designed for specific data models and flexible schemas, they are ideal for large-scale data storage and real-time web applications.
3) Document Stores: Store data as documents, typically in JSON or BSON format. Examples: MongoDB, CouchDB, Firestore.
4) Key-Value Stores: Store data as key-value pairs, offering high performance for simple queries. Main of them are Redis, DynamoDB, Memcached.
5) Column-Family Stores: Organize data into columns and rows, optimized for read and write performance. Main of them are Cassandra, HBase, Bigtable.
6) Graph Databases: Designed to handle data with complex relationships, representing it as nodes, edges, and properties. Main of them are Neo4j, Amazon Neptune, OrientDB.
7) Time Series Databases: Optimized for handling time series data, such as logs and sensor data, providing efficient querying and storage. Main of them are InfluxDB, TimescaleDB, Prometheus.
8 ) NewSQL Databases: Combine the scalability of NoSQL with the ACID guarantees of traditional relational databases. Main of them are Google Spanner, CockroachDB, VoltDB.
9) Search Engines: Specialized databases optimized for indexing and searching large datasets, often used for full-text search. Main of them are Elasticsearch, Solr, Algolia.
10) Multi-Model Databases: Support multiple data models (e.g., document, graph, key-value) within a single database engine. Main of them are ArangoDB, Cosmos DB, MarkLogic.
11) Vector Databases: Optimized for handling vector data, often used in AI and machine learning applications. Main of them are Pinecone, Weaviate, Milvus.
12) Legacy Databases: Older database systems that have been widely used historically and may still be in use today for certain applications. Main of them are IBM IMS, dBASE, Microsoft Access.
This mindmap serves as a comprehensive guide to understanding the diverse landscape of database technologies available today, helping in selecting the right database based on specific requirements and use cases.
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