NoSQL vs. SQL Databases: A Comprehensive Overview
If you are looking to grow in you tech career and understand system design indepth, this guide is for you.
TL;DR
NoSQL databases, developed in the late 2000s, focus on scalability, fast queries, ease of application changes, and simpler programming for developers. In contrast, SQL databases, originating in the 1970s, aim to reduce data duplication and typically require expensive vertical scaling. SQL databases have rigid, complex schemas, while NoSQL databases offer flexible, schema-less structures.
Overview
This article covers:
- Differences between SQL and NoSQL databases
- Benefits of NoSQL databases
- Drawbacks of NoSQL databases
- How to try a NoSQL database
Differences Between SQL and NoSQL
The table below summarizes the main differences between SQL and NoSQL databases.
| Aspect | SQL Databases | NoSQL Databases |
|---|---|---|
| Data Storage Model | Tables with fixed rows and columns | Document: JSON documents, Key-value: key-value pairs, Wide-column: tables with dynamic columns, Graph: nodes and edges |
| Development History | Developed in the 1970s to reduce data duplication | Developed in the late 2000s for scalability and rapid application changes driven by agile and DevOps practices |
| Examples | Oracle, MySQL, Microsoft SQL Server, PostgreSQL | Document: MongoDB, CouchDB; Key-value: Redis, DynamoDB; Wide-column: Cassandra, HBase; Graph: Neo4j, Amazon Neptune |
| Primary Purpose | General purpose | Varies: general purpose, large data with simple queries, predictable query patterns, analyzing relationships |
| Schemas | Rigid | Flexible |
| Scaling | Vertical (scale-up) | Horizontal (scale-out) |
| Multi-Record ACID Transactions | Supported | Mostly unsupported, some like MongoDB support them |
| Joins | Typically required | Typically not required |
| Data to Object Mapping | Requires ORM (Object-Relational Mapping) | Often not required, e.g., MongoDB documents map directly to programming language data structures |
Benefits of NoSQL Databases
Flexible Data Models
NoSQL databases offer flexible schemas, allowing for easy modifications as requirements evolve. This flexibility facilitates rapid iteration and continuous integration of new application features.
Horizontal Scaling
Unlike SQL databases that often require vertical scaling (migrating to a larger, more expensive server), NoSQL databases allow horizontal scaling. This involves adding more commodity servers to handle increased load.
Fast Queries
NoSQL databases often provide faster query performance because data is stored in a way that optimizes queries. Unlike SQL databases, which often require joins across normalized tables, NoSQL databases store related data together, reducing the need for joins and speeding up queries.
Developer-Friendly
Some NoSQL databases, like MongoDB, map their data structures directly to popular programming languages. This mapping simplifies development by allowing developers to work with data in a more intuitive way, reducing code complexity and potential bugs.
Drawbacks of NoSQL Databases
Lack of Multi-Document ACID Transactions
Many NoSQL databases do not support ACID (Atomicity, Consistency, Isolation, Durability) transactions across multiple documents. While single-record atomicity is sufficient for many applications, some require ACID transactions across multiple records. MongoDB has addressed this with multi-document ACID transactions in its 4.0 release, further enhanced in 4.2 for sharded clusters.
Larger Data Footprint
NoSQL databases, optimized for query performance rather than minimizing data duplication, can require more storage space than SQL databases. While storage costs are relatively low, some NoSQL databases support compression to mitigate this drawback.
Use Case Specificity
Different types of NoSQL databases are tailored to specific use cases. For example, graph databases excel at analyzing data relationships but may not be ideal for general data retrieval. Selecting the appropriate NoSQL database depends on the specific use cases and requirements.
How to Try a NoSQL Database
MongoDB
To explore NoSQL databases, MongoDB is a great starting point. You can read the Where to Use MongoDB white paper to determine if MongoDB or another database suits your needs. Then, learn about the document model in the What Is a Document Database? guide.
MongoDB Atlas
For hands-on experience, use MongoDB Atlas, a fully managed global database service available on all leading cloud providers. Atlas offers a free tier, enabling you to create and experiment with databases without a credit card.
MongoDB University
For structured learning, MongoDB University provides free online training, guiding you step-by-step through MongoDB.
Quick Start Tutorials
Once ready to interact with MongoDB using your preferred programming language, check out the Quick Start Tutorials. These tutorials will help you get up and running quickly.
By understanding and leveraging the benefits of NoSQL databases, you can build scalable, efficient, and developer friendly applications.
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Last updated 17 Aug 2024, 12:31 +0200 .