HON95-wiki/soft-eng/dbmses.md

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title: Database Management Systems (DBMSes) breadcrumbs:

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A very brief comparison of different database management systems (DBMSes).

Relational DBMSes (RDBMSes)

• RDBMSes are based on tables consisting of rows and columns, and it thus apropriate for structured data.
• RDBMSes require the core properties atomicity, consistency, isolation and durability (ACID).
• Normalization is heavily used (by the user) to remove data redundancy.
• The need for consistency (and other properties) may hinder horizontal scaling.
• Most RDBMSes use their own variation of standard SQL, with both extra and missing features.

SQLite

• Open-source.
• Lightweight and portable.
• Serverless and backed by a single file, which makes it very simple to configure and use.
• No users or access control.
• Low memory requirements, making it appropriate for memory constrained enviromnents.
• Limited concurrency, although multiple processes can read the DB file simultaneously.
• Can be used entirely in memory, e.g. for testing.

MySQL

• Dual-licensed as open-source and proprietary. Acquired by Oracle Corporation.
• Very popular with a huge amount of community support and 3rd-party tools.
• Focused more on speed than SQL compliance.
• Server-based with users and access control.
• Supports replication, for increased reliability and horizontal scaling.
• Not fully SQL compliant, lacking support for certain features.
• Limited support for replication.

Object-Oriented DBMSes (OODBMSes)

• OODBMSes are based on objects from object-oriented programming and thus allows using a common representation and environment in both the application layer and database layer without the need for querying the data (unlike RDBMSes).

Object-Relational DBMSes (ORDBMSes)

• ORDBMSes are a hybrid of OODBMSes and RDBMSes which contains features from both.
• Unline pure RDBMSes, they may support (e.g.) inheritance and custom data types.

PostgreSQL

• Open-source and community-driven.
• Object-relational DBMS (ORDBMS).
• Server-based with users and access control.
• Focused more on SQL compliance and features than speed.
• Better concurrent read-write performance than MySQL, but less performant for simple read-heavy traffic.

NoSQL

• NoSQL is an umbrella term for non-relational DBMSes and thus consists of many different categories.
• It's aimed at non-structured data that wouldn't fit nicely in a (relational) table.
• OODBMSes may technically be considered NoSQL, but they often contain features which make them more similar to RDBMSes.
• While RDBMSes rely on strict consistency, NoSQL aims for eventual consistency, meaning it allows data changes to reach all database nodes in a short time rather than instantaneously. This means that the data received from the database(s) may in some cases be slightly outdated.

Key-Value Stores

• Generally consists of an associative array of unstructured/blob values indexed by unique keys.
• Typically used for data caching and message queueing.
• Examples:
  • Memcached
  • Redis

Columnar-Oriented Databases

• Similar to RDBMSes, but splits all columns into different files. This allows for certain types of optimizations, which may improve both storage and querying for certain application types.
• Examples:
  • Apache Cassandra
  • Apache HBase

Document-Oriented Databases

• Aka document stores.
• A special type of key-value stores with documents as values, but contains metadata about the document as well.
• May allow nesting of documents.
• Examples:
  • MongoDB
  • Couchbase
  • Apache CouchDB

Graph Databases

• Document-oriented databases which use graph theort to relate documents.
• Useful for applications where relations in the data are of interest.
• Examples:
  • Neo4j
  • ArangoDB
  • OrientDB

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