Use Cases

What kinds of applications and workloads 14 popular databases are typically chosen for.

PostgreSQL

A strong general-purpose choice for OLTP applications and complex analytical queries alike, favored when teams need rich SQL, strong consistency, and extensions like PostGIS for geospatial workloads.

MySQL

Common in web applications, content management systems, and e-commerce platforms, particularly where read-heavy workloads, simplicity, and broad managed-hosting support are priorities.

SQLite

Well suited to embedded and mobile apps, local-first software, automated testing, and edge/serverless functions — anywhere a full client-server database would be unnecessary overhead.

MongoDB

Popular for content catalogs, product catalogs, and applications with evolving or deeply nested document structures, where rapid iteration on data shape matters more than rigid schema enforcement.

Redis

Widely used as a caching layer, session store, and backing store for real-time features like leaderboards and rate limiting, as well as lightweight pub/sub messaging and queues.

Cassandra

Fits write-heavy time-series and IoT data, and applications spanning multiple datacenters that need to stay available even during partial outages, at the cost of strict consistency.

DynamoDB

A natural fit for serverless, AWS-native applications that need predictable low-latency access at very large scale, common in gaming and ad-tech workloads.

CockroachDB

Chosen for globally distributed applications that need both strong consistency and horizontal scale, including financial and other regulated systems that require geo-partitioned data.

MariaDB

Often used as a drop-in MySQL replacement in open-source-first environments, particularly where teams want to avoid Oracle’s MySQL licensing terms while keeping a familiar relational workflow.

Oracle Database

Deployed heavily in large enterprises for OLTP and data warehousing, especially mission-critical financial and ERP systems that require vendor support and strict compliance guarantees.

SQL Server

Common in enterprises standardized on the Microsoft stack, integrating tightly with business-intelligence tools like SSRS and SSAS and with .NET-centric application development.

Elasticsearch

The go-to choice for full-text search, log and event analytics (as in the ELK stack), observability platforms, and features like autocomplete or relevance-ranked search.

Neo4j

Suited to problems that are naturally graph-shaped: fraud detection, recommendation engines, social networks, and knowledge graphs where relationships between entities are as important as the entities themselves.

Firestore

A common backend for mobile and web apps that need real-time data sync, offline support, and serverless auto-scaling with minimal operational overhead, especially within the Firebase ecosystem.