Evolution of Databases: From Traditional to Distributed Systems

Traditional relational databases

Relational databases are built on a data structure in the form of tables. Each table has attributes (columns) with data characteristics, and tuples (rows) that represent specific data instances.

The standard query language for working with such databases is SQL (Structured Query Language). It allows you to perform various operations, such as adding, deleting, updating and selecting data from the database.

Relational databases are usually horizontally scalable. This means that they can be scaled up by adding new servers or nodes to process more data.

This type of database provides a reliable and structured way to store and manage data. However, they can have their limitations, which become more apparent as data volumes and requirements for availability and scalability grow. Let's take a look at some of them:

• Complexity of data modeling
  Relational databases do not always effectively model scenarios with complex relationships or a large number of tables.
• Limited scalability
  Handling large amounts of data and a large number of simultaneous users can lead to performance degradation and problems with operations.
• Lack of flexibility
  The complexity of making changes to the data structure or queries without redesigning the entire system can slow down adaptation to changes in user needs or business requirements.

Distributed databases

Distributed databases are systems that allow you to store and process large amounts of data on several physically remote servers with shared access to them via a network.

Data distribution between different nodes ensures high availability, scalability and reliability of the system. Each node can have its own local copy of the data and process requests without sharing data with other nodes.

An important aspect of distributed databases is ensuring data consistency between different nodes and executing transactions in a distributed environment.

Distributed database technologies are widely used in corporate, financial and telecommunications systems, cloud services, social networks, etc.

Trends in distributed database development

Cloud solutions

Cloud-based distributed database solutions allow companies to store and process their data in virtual environments. This simplifies the deployment, scaling and management of databases without significant hardware and maintenance costs.

Expanding functionality

The functionality of distributed databases includes additional capabilities for storing and processing geospatial data, texts, images, video and audio. Also, support for analytical functions, machine learning, and intelligent algorithms for analyzing large amounts of data is being improved.

Integration with other technologies

The integration of distributed databases with artificial intelligence, machine learning and blockchain technologies allows you to create powerful and innovative applications that use data from various sources.

Automation 

Implementation of intelligent algorithms allows you to automate the processes of managing and optimizing the database. This can include automatic scaling, load balancing, data replication, monitoring and resource management. Automation simplifies the administration and support of distributed systems with minimal human intervention.

The development of distributed databases is taking place against the backdrop of growing needs for fast and reliable access to large amounts of data. Ensuring flexibility, scalability and security are the main challenges for the development of this industry.

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