← Back to Technologies

Database Technologies

Explore our comprehensive database technology stack that powers innovative solutions

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

Microsoft SQL Server

Microsoft SQL Server is a powerful relational database management system designed for high performance, reliability, and scalability. It offers advanced security features, robust reporting tools, and seamless integration with other Microsoft products.

Key Features

  • ACID compliance
  • Advanced security features (TDE, Always Encrypted)
  • Integration with Microsoft Azure
  • Comprehensive reporting and analytics tools

Common Use Cases

  • Enterprise-level applications
  • Data warehousing
  • Business intelligence platforms
  • Real-time transaction processing

Benefits

  • High availability and disaster recovery
  • Robust security and compliance
  • Seamless integration with Microsoft products
  • Scalability for large datasets and high transaction volumes

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

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

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

Elasticsearch

Elasticsearch is a distributed search and analytics engine built on top of Apache Lucene. It is widely used for powering search functionalities and real-time analytics in diverse applications.

Key Features

  • Full-text search capabilities
  • Distributed architecture
  • Scalable and fault-tolerant
  • Real-time data indexing

Common Use Cases

  • Enterprise search systems
  • Log and event monitoring
  • E-commerce product search
  • Real-time analytics platforms

Benefits

  • Fast and accurate search results
  • Handles large-scale data
  • Customizable for specific use cases
  • Integration with other tools in the ELK stack