NoSQLmotorer

NoSQLmotorer is a term used to describe a family of database engines optimized for NoSQL data models. They are designed to store and retrieve data without fixed schemas, support horizontal scalability, and operate in distributed environments.

NoSQLmotorer typically categorize into four main data models: key-value stores, document stores, column-family stores, and graph databases. Some engines combine models in a multi-model approach, enabling flexible storage for different application needs.

They achieve scalability through sharding and replication across clusters. They often favor eventual consistency or tunable consistency to maximize availability and throughput, in line with the CAP theorem.

Querying and transactions vary by engine. Many provide APIs or domain-specific query languages, some offer SQL-like layers, while others rely on map-reduce, graph queries, or simple key-based access. Cross-record transactions are limited in many systems, with some newer engines offering multi-document ACID transactions.

Usage scenarios include real-time analytics, content catalogs, user profiles, IoT telemetry, caching, and social graphs. Trade-offs commonly involve fewer joins and more complex transactions, as well as tooling maturity and potential data duplication.

History and landscape: NoSQLmotorer emerged in the early 2000s to address web-scale workloads and polyglot data models. Notable examples across the family include MongoDB (document), Cassandra and HBase (column-family), Redis (key-value), and Neo4j (graph).