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Database Technologies

Explore our database stack technologic that powers innovative solutions

MongoDB

MongoDB is a NoSQL database designed to handle unstructured or semi-structured data efficiently. Its document-based model allows for flexibility and scalability in modern applications.

Key Features

  • •Document-based schema
  • •Horizontal scaling with sharding
  • •Built-in aggregation framework
  • •Support for ACID transactions

Common Use Cases

  • •Real-time analytics
  • •Content management systems
  • •IoT applications
  • •Mobile and web apps

Benefits

  • •Flexible schema design
  • •High scalability
  • •Faster development cycles
  • •Seamless integration with modern tools

MySQL

MySQL is a leading open-source relational database, highly regarded for its performance, ease of use, and reliability. It powers many modern web applications and services.

Key Features

  • •Cross-platform compatibility
  • •Support for SQL and stored procedures
  • •Replication for high availability
  • •High-performance indexing

Common Use Cases

  • •Web applications
  • •E-commerce platforms
  • •CMS (Content Management Systems)
  • •Data warehousing

Benefits

  • •Ease of setup and maintenance
  • •Scalable architecture
  • •Strong community support
  • •Cost-effective solution

PostgreSQL

PostgreSQL is our preferred relational database for its robustness, feature set, and reliability. It provides advanced features like JSON support, full-text search, and excellent performance for complex queries.

Key Features

  • •ACID compliance
  • •JSON and JSONB support
  • •Full-text search capabilities
  • •Advanced indexing options

Common Use Cases

  • •Complex data relationships
  • •Geographic applications
  • •Financial systems
  • •Analytics platforms

Benefits

  • •Data integrity and reliability
  • •Excellent performance
  • •Strong community support
  • •Enterprise-ready features

Redis

Redis is a fast, in-memory key-value store and database, often used for caching, real-time analytics, and session management in high-performance applications.

Key Features

  • •Sub-millisecond latency
  • •Data structures like hashes, lists, and sets
  • •Persistence options (snapshotting and AOF)
  • •Pub/Sub messaging system

Common Use Cases

  • •Caching for web applications
  • •Real-time analytics
  • •Session management
  • •Message brokering

Benefits

  • •Blazing fast data access
  • •Reduced backend workload
  • •Scalable for large-scale systems
  • •Wide range of use-case versatility

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