A distributed database is a collection of logically interconnected databases that are physically distributed across multiple geographic locations, interconnected by a computer network. In a distributed database system, the data is stored across several independent data processing nodes in a coordinated and unified manner. Each node may consist of a separate database server or a cluster of servers, running a database management system (DBMS) to handle local data processing and storage tasks. This advanced database architecture offers significant benefits regarding data availability, fault tolerance, performance, and scalability.
In the context of modern software development, distributed databases have become a widely adopted approach to handling large volumes of data, especially in the age of big data and the internet of things (IoT). The driving forces behind the increasing popularity of distributed databases are the rapid growth of data volume, velocity, and variety and the need for highly available and fault-tolerant systems that provide low-latency access to the data.
One of the key challenges in designing and implementing a distributed database system is maintaining data consistency and coherence across the multiple data nodes. To address this challenge, distributed databases employ various synchronization and replication strategies, such as strict consistency, eventual consistency, and tunable consistency. These strategies define how the system ensures the data between nodes is updated and synchronized promptly and accurately.
AppMaster, a no-code platform for creating backend, web, and mobile applications, uses distributed databases for hosting data of its users and applications. AppMaster's platform is designed to work with any PostgreSQL-compatible primary database to provide the required data capabilities for enterprises and high-load use cases. Given its real-time and scalable nature, AppMaster allows users to maintain high data availability, consistency, and integrity across all applications supported by the platform.
Distributed database systems can be categorized into different types according to their architecture, data storage, and distribution models, such as:
- Fragmentation - dividing the database into smaller pieces (fragments) and distributing them across the nodes.
- Replication - maintaining multiple copies of the same data in different nodes to ensure high availability and fault tolerance.
- Sharding - partitioning the database into horizontal subsets (shards) and distributing them across nodes. Each shard holds a unique subset of data; all shards constitute the entire database.
- Federated - integrating several independent databases with a centralized management and query processing system.
Moreover, distributed database systems can be classified based on the levels of transparency they achieve, such as:
- Data transparency - abstracting the physical distribution of data from users and applications. Users interact with the system as if it were a single, centralized database.
- Transaction transparency - providing a unified transaction model that spans over multiple nodes. The system ensures distributed transactions are atomic, consistent, isolated, and durable (ACID).
- Performance transparency - reducing the impact of data distribution on system performance by employing mechanisms such as caching, optimization, and load balancing.
There has been a growing interest in using distributed ledger technologies, such as blockchain, to implement distributed databases in recent years. Blockchain-based distributed databases offer enhanced data integrity, security, and trust by design, as their transactional records are immutably stored and cryptographically verified in a decentralized network of nodes.
A distributed database is an advanced data management system that addresses the challenges and requirements of modern software applications, including distributed and high-performance computing, big data, and IoT. Distributed databases offer several advantages, such as data availability, fault tolerance, scalability, and performance, by storing and processing the data in a coordinated and unified manner across a network of interconnected nodes. AppMaster, the no-code platform for creating backend, web, and mobile applications, supports distributed database capabilities to ensure high levels of data availability, consistency, and integrity across all applications built on the platform. With various types, architectures, and transparency levels, distributed databases continue to evolve and drive innovations in data management and software development.
