BD Compare Q & A

Post by ailswan Jan. 07, 2024

BD Compare Q & A

Date: January 07, 2024 Tags: Backend , Review-Q&A

BD Compare: ProtgreSQL, MySQL, MongoDB and Cassandra Q & A

Feature Comparison Table

Feature PostgreSQL MySQL MongoDB Cassandra
Use Cases Advanced features, complex queries, Traditional relational database Flexible schema, unstructured or Highly scalable, distributed NoSQL
  data integrity applications with structured data semi-structured data, modern web database, suitable for large-scale
    and complex queries, widely used applications with horizontal scaling distributed systems
    in web development    
Scalability Vertical scaling, proper Vertical and horizontal scaling, Horizontal scaling through sharding, Horizontal scaling, designed for
  configuration for large data, suitable for growing applications suitable for large volumes of data distributed and decentralized
  horizontal scaling through   and high traffic systems
  replication      
Consistency Fully ACID compliant with strong ACID compliant with strong Eventual consistency with Tunable consistency levels, designed
  consistency guarantees, suitable consistency guarantees, suitable configurable consistency levels, for high write and read throughput
  for mission-critical applications for applications where data suitable for applications where  
    integrity is crucial real-time consistency is not critical  
Ease of Use Known for complexity, requires Known for ease of use, suitable Known for simplicity and rapid Designed for high write and read
  expertise but provides flexibility for beginners and straightforward development, well-suited for agile throughput, may require expertise
    projects development and startups  
Ecosystem Strong community support, rich set Large and mature ecosystem with Growing ecosystem with a focus on Active community support, suitable
  of extensions, vibrant ecosystem extensive documentation and modern development stacks, active for distributed and decentralized
    community support community support systems
Licensing Open source with PostgreSQL License Open source with GPL or commercial Server Side Public License (SSPL) Open source with Apache License

Detailed Feature Comparison

Feature PostgreSQL MySQL MongoDB Cassandra
Data Integrity Referential integrity, constraints Referential integrity, constraints Validation rules, atomic writes Built-in support for distributed transactions,
        data replication, eventual consistency
Query Language SQL SQL MongoDB Query Language (MQL) CQL (Cassandra Query Language)
Secondary Indexing B-tree, hash, and more B-tree, hash, and more JSON-based secondary indexes, compound indexes Various index types including secondary indexes
Joins and Relationships Supports various types of joins and relationships Supports various types of joins and relationships Limited support for joins and relationships No native support for joins and relationships
ACID Compliance Fully ACID compliant with strong consistency ACID compliant with strong consistency ACID for single documents, multi-document Support for lightweight transactions, eventual
      transactions with snapshot isolation consistency for high throughput
Schema Flexibility Rigid schema, requires predefined structure Rigid schema, requires predefined structure Dynamic schema, accommodates unstructured data Flexible schema design suitable for dynamic data
Indexing Options Various indexing options for different scenarios Various indexing options for different scenarios Automatic and configurable indexing Various index types including secondary indexes
Transactions Supports complex transactions and rollbacks Supports complex transactions and rollbacks Limited multi-document transactions Support for lightweight transactions, eventual
        consistency for high throughput
Concurrency Control Multi-version concurrency control (MVCC) Multi-version concurrency control (MVCC) Optimistic concurrency control Optimistic concurrency control
Data Distribution Can be configured for distributed databases Can be configured for distributed databases Sharding for horizontal data distribution Designed for distributed and decentralized
        data distribution
Partitioning Table partitioning options Table partitioning options Sharding for horizontal data partitioning Automatic data partitioning and distribution
Performance Tuning Fine-grained control over performance tuning Comprehensive performance tuning options Automatic performance tuning and optimization Tunable consistency levels, performance
        optimizations for high write and read throughput
Geospatial Support Robust support for geospatial data and queries Basic geospatial support Limited geospatial support Limited geospatial support

Choosing a Database: MySQL vs PostgreSQL vs MongoDB

MySQL:

  • Use Cases: Well-suited for traditional relational database applications with structured data and complex queries, widely used in web development.

  • Scalability: Supports both vertical and horizontal scaling, making it suitable for growing applications.

  • Consistency: ACID compliant with strong consistency guarantees, suitable for applications where data integrity is crucial.

  • Ease of Use: Known for its ease of use, making it a good choice for beginners and projects with straightforward requirements.

  • Ecosystem: Large and mature ecosystem with extensive documentation and community support.

  • Licensing: Open source with GPL or commercial options.

PostgreSQL:

  • Use Cases: Ideal for applications requiring advanced features, complex queries, and data integrity. Suitable for geospatial applications and extensive data types.

  • Scalability: Supports vertical scaling, and with proper configuration, it can handle large amounts of data. Horizontal scaling can be achieved through replication.

  • Consistency: Fully ACID compliant with strong consistency guarantees. Suitable for mission-critical applications.

  • Ease of Use: Known for its complexity, but offers advanced features. Requires more expertise but provides flexibility.

  • Ecosystem: Strong community support with a rich set of extensions and a vibrant ecosystem.

  • Licensing: Open source with the PostgreSQL License.

MongoDB:

  • Use Cases: Best for applications with flexible schema requirements, unstructured or semi-structured data, and the need for horizontal scaling. Well-suited for modern web applications.

  • Scalability: Horizontal scaling through sharding makes it suitable for handling large volumes of data and high traffic.

  • Consistency: Eventual consistency with configurable consistency levels. Suitable for applications where real-time consistency is not critical.

  • Ease of Use: Known for its simplicity and rapid development. Well-suited for agile development and startups.

  • Ecosystem: Growing ecosystem with a focus on modern development stacks. Active community support.

  • Licensing: Server Side Public License (SSPL).

Considerations for All:

  • Data Structure: MySQL and PostgreSQL are relational databases with tables and structured data, while MongoDB is a NoSQL document-oriented database.

  • Scalability Requirements: Consider whether your application needs vertical or horizontal scaling, and the level of scalability each database offers.

  • ACID Compliance: Consider the level of transactional support required for your application.

  • Ease of Use vs. Advanced Features: Evaluate the trade-off between ease of use and the need for advanced features based on your project requirements and team expertise.

  • Community and Support: Assess the strength and activity of the community, as well as the availability of support and documentation.

  • Licensing: Consider the licensing model and whether it aligns with your project’s goals.

Conclusion: The choice depends on the specific needs of your project, the nature of your data, and your team’s expertise. Run small-scale tests with each database to assess performance and ease of use based on your unique requirements.