If you are new to the blockchain ecosystem, you have heard of distributed systems. Indeed, distributed databases are one such example where a collection of databases work together to provide a single, unified database. It helps to distribute data processing and storage across multiple machines or nodes, providing better performance, scalability, and fault tolerance. In the time of artificial intelligence and blockchain technology, an efficient distributed database plays a crucial role. In this blog, I am going to explore the ten key fundamental principles of distributed databases.

Fundamental Principles of Distributed Database

Safe Distribution of Data

The distribution is the basic principle of distributed databases. It refers to the ability to store and access data across multiple locations, systems, or networks. Data distribution enables the system to achieve better performance and reliability by distributing data across multiple servers or nodes.

Simple and Transparency Data Processing

It refers to the ability of the system to hide the complexity of data distribution from the users. The system should appear to the user as a single database, even though it is distributed across multiple locations and systems. Transparency ensures that users do not need to know where the data is stored, which machine is processing their query, or any other technical details. You can also consider it a user-friendly system!

Integrity and Consistency of Data Structure

It maintains the integrity and accuracy of data across all nodes in the system. Consistency ensures that all users see the same data, regardless of the node they access. It is essential for a blockchain technology. There are two types of consistency: strong consistency and eventual consistency.

  • Strong consistency requires that all nodes in the system see the same data at the same time. It means all nodes have the same view of the data, but it can be expensive in terms of performance.
  • Eventual consistency allows nodes to have different views of the data for a short period. However, the system eventually ensures that all nodes converge to the same view of the data. This approach is more efficient but can lead to temporary inconsistencies in the system.

Easy Access to Data and Services

Distributed databases allow easy access to data and services at all times, even in the time of a system failure or outage. It must ensure that data and services are available and accessible to users at all times. How is it possible? It uses techniques like redundancy, fault tolerance, and disaster recovery mechanisms.

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Partitioning is Essential for Easy Distribution

Partitioning is a principle that enables distributed databases to scale horizontally by dividing data into smaller segments or partitions and distributing them across multiple nodes or servers. Partitioning enables the system to handle large amounts of data and scale up or down as needed. It helps to access and understand vast data sets easily. There are several types of partitioning, including range partitioning, hash partitioning, and list partitioning.

  • Range partitioning involves partitioning data based on a specified range of values. For example, customer data can be partitioned based on the value of their account number.
  • Hash partitioning involves partitioning data based on a hash function. This ensures that data is evenly distributed across all nodes in the system.
  • List partitioning involves partitioning data based on a predefined list of values. For example, you can use the geographical location of your customer base for partition.

Replication Avoids Issues During Nodes Failure

Replication is a principle that involves creating multiple copies of data and distributing them across multiple nodes or servers in the system. Replication ensures data availability and fault tolerance by ensuring that data is always accessible, even if one or more nodes fail.

There are two types of replications: synchronous replication and asynchronous replication.

  • Synchronous replication involves replicating data to all nodes in the system simultaneously. It ensures that all nodes have the same view of the data.
  • Asynchronous replication involves replicating data to all nodes in the system at a later time. It is a more efficient approach.

Perform Distributed Query Processing

One of the significant advantages of distributed databases is the ability to perform distributed query processing. Query processing refers to the process of translating user requests into queries that the database can understand and execute.

With distributed query processing, queries can be executed simultaneously on multiple nodes, which enhances the system’s performance. However, it is also important to ensure the query processor optimizes queries for execution on different nodes and manages the flow of data between nodes.

Concurrency Control During Data Modification

Concurrency control is an essential principle of distributed databases. It refers to the ability of the system to ensure that multiple users can access and modify the same data simultaneously without creating conflicts or inconsistencies. Distributed concurrency control requires coordination between the different nodes to ensure that data is not overwritten or modified in conflicting ways.

Protect Data from Unauthorized Access

Distributed databases must ensure that data is protected from unauthorized access, modification, and deletion. Security features such as access control, authentication, encryption, and audit trails ensure that sensitive data on the nodes is protected.

Performance Monitoring and Tuning

Finally, it monitors and tunes performance to ensure that the system is operating efficiently. Performance monitoring involves tracking system resources and making changes to optimize performance. Performance tuning involves making adjustments to system parameters and configurations to improve the system’s performance.

I hope these principles outlined in this post provide a foundation for understanding the key features and requirements of distributed databases. As an organization, you need to consider scalability, availability, fault tolerance, consistency and many of the above factors before implementing a distributed database in the form of a private blockchain network. Let the developers know about your requirements and get a secure and transparent blockchain ecosystem for your organization.

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