5 Best Database Management Software in 2024

What is a Database Management Software

• relational;
• hierarchical;
• network systems;
• object-oriented.

• Storage. Ensures organized data storage in tables, rows, and columns for quick retrieval.
• Centralized access. Provides controlled access to data from various locations and devices through a unified interface. The data itself can be located anywhere in the world on any storage medium.
• Manipulation. Users can interact with information within the database in various ways (inserting, updating, changing, deleting, etc.), while maintaining its integrity and consistency.
• Backup and recovery. Simplifies and accelerates the process of creating backups and restoring data from them, effectively protecting the data from damage and destruction.
• Administration. Allows management of database versions, monitoring and tuning their performance. Moreover, it enables automatic rollback and reboot, conducting activity audits, and so forth.
  

• Structuring. Systems logically structure data. This is especially useful for processing large volumes of information.
• Integrity and concurrency. Users and developers can simultaneously use the same data, maintaining its integrity.
• Centralization. Ensures data independence and security. In addition, DBMSs provide a locking mechanism, a handler for balancing the needs of multiple client applications, rapid recovery, and more.
• Shared access. Ensures stable shared access to data by many users and applications. It reduces data redundancy, which occurs when storing data in different locations.
• Modification. DBMSs are easier and faster to adapt to specific business requirements. An administrator can add new data categories to the database without affecting the operation of integrated applications.
  

Google Cloud SQL

• The system automates database management processes including patching, encryption, backup, replication, scaling, and more.
• Automatic failover across zones ensures the fastest and most stable access with protection against outages.
• The Enterprise version provides an SLA of 99.95% uptime for general-purpose workloads. The Enterprise Plus version guarantees an SLA of 99.99% for the most resource-intensive tasks, as well as disaster recovery with no data loss.
• The built-in AI assistant, Gemini, speeds up and simplifies a range of database operations: development, performance optimization, management, migration, data collection, and analysis.
• Cloud SQL supports popular open-source and commercial engines, including SQL Server, MySQL, and PostgreSQL. Furthermore, it offers a variety of extensions, configurations, and developer tools.
• The DBMS seamlessly integrates with other Google Cloud services like Compute Engine, Cloud Run, Google Kubernetes Engine, and Cloud IAM. This allows developers to easily and quickly migrate databases without additional costs. Moreover, they have the opportunity to use the service to build and deploy applications using APIs and third-party tools.
  

Microsoft SQL Server

• The cloud version of the DBMS software is available as part of Microsoft Azure tools in the form of PaaS (Platform-as-a-Service) and through Azure SQL Edge for Internet of Things devices. For on-premises use, the scalable hybrid platform SQL Server 2022 is suitable, which includes free Developer and Express versions.
  
• Centralized data management using Azure optimizes database operations and ensures stable, continuous application performance.
• The service's capabilities allow developers to use any technology, including open source. With an impressive set of features, they can easily integrate data into applications.
• Microsoft Data Platform has incorporated AI and ML algorithms into the database structure and peripheral processes, providing rapid forecasting and enhanced protection.
  

MongoDB

• MongoDB's architecture is based on collections and documents, rather than the tables and rows typical of relational databases. Documents contain key-value pairs, and collections organize sets of documents. The platform supports programming languages such as C, C++, C#, Go, Java, Python, Ruby, and Swift.
• MongoDB is suitable for storing large volumes of structured and unstructured data with both vertical and horizontal scaling. It allows data searching by fields, expressions, and ranges.
• The DBMS flexibly integrates data for applications, including hybrid and multi-cloud setups. Load balancing enables its use across multiple servers.
• In document-oriented systems, documents can be embedded to describe nested structures and modify the data stored in them.
• MongoDB offers replication – creating multiple instances of the DBMS consisting of primary and secondary servers. The primary servers handle read and write operations, while the secondary servers store data copies, ensuring high availability.
• The platform supports various data storage engines, as well as the integration of third-party engines via APIs.

• Shared (starting from $0 per month). Provides a basic configuration for learning and using the DBMS in a cloud environment. Space: from 512 MB to 5 GB.
• Serverless (starting from $0.1 per million reads). Suitable for serverless applications with moderate traffic. Minimal setup required. Space: up to 1 TB.
• Dedicated (starting from $57 per month). Designed for production applications with high load requirements. Users gain extended functionality for configuration management. Space: from 10 GB to 4 TB.
  

Snowflake

• Multi-cloud software supported by three major providers: Amazon Web Services, Google Cloud, and Microsoft Azure.
• A multi-cluster data architecture separates computing resources from storage resources. This allows the system to be scaled easily in any direction without compromising its performance.
• The system supports semi-structured data using the VARIANT method to load, process, and transform it into a structured type.
• Snowflake automatically encrypts data with object-level access control, column-level protection, and row access policies.
• Users can share data with other account holders and external clients without duplication and additional payments. Account holders with shared data access only pay for query processing, while the data itself synchronizes with the main source.
• The platform has two different interfaces: Classic Console (with advanced features) and Snowsight (a later-released console focused on an understandable and user-friendly UX).
  

• Standard – starting from $2 per credit.
• Enterprise – starting from $3 per credit.
• Business Critical – starting from $4 per credit.
• Virtual Private Snowflake (VPS) – pricing is calculated individually and provided upon request.
  

Redis

• The platform-managed databases easily integrate into any technology stack, allowing developers to effortlessly create, scale, and deploy applications.
• The system enables rapid deployment of applications in caching, NoSQL, vector databases, and custom configurations in any environment without additional setup.
• Redis supports advanced caching technologies, including a query mechanism, a unified data model, and its own ecosystem with protocols, documentation, and other resources.
• The DBMS ensures enterprise-level security by providing complete control over shared data access and expert support.
• Developers can linearly scale real-time applications with millisecond latency and an SLA of up to 99.999%.
• Support for multi-user mode and automatic multi-tier distribution helps maximize infrastructure efficiency.
  

• Essentials (one database up to 12 GB) – starting from $5 per month.
• Pro (unlimited in number and size of databases) – starting from $0.881 per hour.
  

Final Thoughts

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