Microsoft SQL Server vs MongoDB vs MySQL: What are the differences?
Introduction
This markdown code provides a comparison between Microsoft SQL Server, MongoDB, and MySQL, outlining the key differences between these three popular database management systems.
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Data Model:
- Microsoft SQL Server follows the relational database model, where data is organized in tables with predefined structures and relationships between tables. It ensures data integrity and provides ACID properties.
- MongoDB follows the NoSQL document database model, where data is stored in flexible, schema-less documents (usually JSON format). It allows dynamic and hierarchical data structures, making it more suitable for handling complex data and unstructured data.
- MySQL is also a relational database management system, similar to SQL Server, but it is open source and commonly used for web applications. It provides ACID properties and suitable for traditional tabular data with structured relationships.
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Scalability:
- SQL Server and MySQL are primarily designed for scaling vertically, meaning increasing the capacity of the server by adding more hardware resources.
- MongoDB, on the other hand, follows a distributed architecture and is designed for horizontal scalability. It allows scaling horizontally by adding more servers, distributing the data across a cluster, and handling large-scale applications with increased performance.
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Language for Querying:
- SQL Server and MySQL use SQL (Structured Query Language) for querying and manipulating data. SQL provides a standardized way to interact with relational databases using declarative statements.
- MongoDB uses a flexible query language based on JavaScript, allowing querying by fields, ranges, regular expressions, and complex conditions. It also provides a powerful aggregation framework for data processing and analysis.
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Schema
- SQL Server and MySQL use a predefined schema, where tables and fields must follow a predefined structure. Any modifications to the schema require altering the table structure.
- MongoDB is schema-less, allowing dynamic and flexible structures within the same collection. Each document can have a different structure, and new fields can be added without requiring a predefined schema change.
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Transactions and ACID properties:
- SQL Server and MySQL provide strong support for transactions and ACID properties (Atomicity, Consistency, Isolation, Durability). They ensure data consistency and reliability.
- MongoDB supports atomic operations at the document level but does not provide full ACID transactions. It favors eventual consistency and provides the option to implement multi-document transactions using the new WiredTiger storage engine in certain cases.
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Data Scaling Limits:
- SQL Server and MySQL have certain limits on the maximum database size and number of connections. MySQL allows up to 2^32 (4,294,967,296) rows per table and a maximum database size of 64TB.
- MongoDB has a flexible document structure, and its maximum document size is 16MB. However, it allows sharding, enabling scaling the data across multiple servers and effectively removing the limit on overall data capacity.
In summary, SQL Server and MySQL are relational databases suitable for structured data and traditional applications, while MongoDB is a flexible NoSQL document database more suitable for handling unstructured and complex data with horizontal scalability.
