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Databases serve as the backbone for businesses of all sizes, from agile startups to global enterprises.

The right choice of database software can significantly impact business performance, scalability, and operational efficiency.

With so many options available, how do you choose the right one?

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Relational databases are ideal for structured data and are widely used in banking, e-commerce, and ERP systems.

RDBMSs adhere to ACID properties (Atomicity, Consistency, Isolation, Durability) to ensure reliable transaction processing.

Some popular RDBMS are MySQL, PostgreSQL, Oracle Database, Microsoft SQL Server, and SQLite.

Additionally, the market was valued at USD 70.76 billion in 2024.

The table below provides an overview of popular relational databases, highlighting their key features and ideal use cases.

It supports different data models, including key-value, document, column family, and graph.

They also provide easy replication, making them more resistant to unplanned outages and disruptions.

The table below provides an overview of popular NoSQL databases, showcasing their standout features and best-fit use cases.

It offers high availability, security, and automated backups.

It organizes and stores structured, unstructured, and semi-structured data.

you’re able to launch or shut down a cloud database in minutes.

They also scale automatically, ensuring smooth performance even as your workload increases.

Types of Cloud Databases

Cloud databases fall into two main categories:relationalandnon-relationaldatabases.

They follow a fixed schema and use SQL to query and manage data.

Examples: SQL Server, Oracle, MySQL, PostgreSQL, Spanner, and Cloud SQL.

Examples: MongoDB, Redis, Cassandra, HBase, and Bigtable.

The table below overviews popular cloud databases, showcasing their key features and ideal use cases.

They offer remote access, scalability, automated backups, and real-time collaboration.

They are commonly used in businesses, e-commerce, SaaS applications, and data-driven projects.

Google Firebase, Amazon RDS, Microsoft Azure SQL Database, and Airtable are popular options.

The table below overviews popular online databases, highlighting their key features and ideal use cases.

Some popular OODBs are db4o, ObjectDB, and Action NoSQL.

The table below overviews popular OODBs, highlighting their key features and ideal use cases.

Graph Database

A graph database is a NoSQL database built to handle highly connected data.

Nodes function like rows in relational databases and can be categorized with labels.

Edges establish structured connections with a defined start, end, key in, and direction.

Properties add contextual data, making graph databases highly efficient for modeling complex relationships.

They deliver faster queries by directly traversing connections rather than performing expensive table joins.

Some popular graph databases are Neo4j, ArangoDB, TigerGraph, and Amazon Neptune.

The table below overviews popular graph databases, highlighting their key features and ideal use cases.

It enhances scalability, availability, and fault tolerance by replicating or partitioning data across different nodes.

Some popular examples are Google Cloud Spanner, Amazon Aurora, Apache Cassandra, and CockroachDB.

The table below overviews popular distributed databases, highlighting their key features and ideal use cases.

Its perfect for low latency and high-speed applications, like real-time analytics, caching, and financial transactions.

Since IMDBs bypass disk storage, theyre much faster than traditional databases.

These databases are best for handling high-speed data access where some data loss is acceptable.

The table below overviews popular In-memory databases, showcasing their key features and ideal use cases.

TSDBs help you handle large amounts of time-stamped data efficiently.

TSDBs store time data as timestamps with second or millisecond precision.

They support different date formats, time zones, and calendar adjustments.

With built-in compression algorithms, TSDBs ensure fast query responseseven for large datasets.

The table below overviews popular TSDBs, showcasing their key features and ideal use cases.

While they excel in speed and simplicity, they often lack features like multi-user access and advanced queries.