In the Current world, Data is the new gold or oil for many organizations. It is a lifeline for many businesses as it provides valuable information to a different line of business. An organization can have various types of data stored in persisted storage like a database. In order to do that, one needs a database that can meet the growing need of the organization. As a normal database cannot withstand the high volume of data that gets generated nowadays, organizations are resorting to distributed databases that allow storing the needed data in the right format.
What is a Distributed Database?
A distributed database is a group of databases that are spread physically across various locations and are connected together by a data communications network. As the databases are all connected together, they perform and act like a single logical unit of databases.
Administrative tasks of the distributed database are executed centrally through a corporate IT resource. As the databases are connected through a network, Users at various geographical locations can access the data at different geographical locations. Computers or machine that hosts a distributed database might be a normal PC to a supercomputer.
When data needs to be processed through distributed databases, processing of this data is distributed to various nodes or servers located at various locations. The organization needs to add more nodes to scale the distributed database horizontally. More nodes mean more processing power, high availability, and no single point of failure in the system.
Horizontal scaling is needed to meet the increase in workload requirement without making any changes in the database applications.
Advantages of Distributed Computing
There are many advantages when the distributed database is implemented in an organization.
The following are some advantages.
- High Availability
They are highly available as they continue to function even though one of the nodes fails. It is achieved by applying redundancy and fault-tolerant mechanism in the database.
- Location Agnostic
As data is stored at multiple locations, the database is not dependent on any location as is managed by a centralized and independent Distributed Database Management System(DDBMS)
- Provides a fault-tolerant database system
- Prevents Single Point of Failure(SPOF)
- Consistent
Distribute databases are able to maintain consistency throughout all the nodes in their network. It means changes from one node are propagated to another node, providing the same view of data for all customers.
- Manages Distributed ACID and Non-ACID compliance Transactions
It provides various services like concurrency controls, disaster recovery mechanisms, failure recovery, and commit protocols for handling transactions in both SQL and NoSQL databases.
- Provides high throughput
- Low Latency with geographically distributed server
- Highly Scalable as it scales horizontally
They are highly scalable as they are able to add more nodes to the network horizontally, enabling them to handle high-traffic loads.
- Distributed Query Processing
In a distributed database, queries are processed in a distributed fashion by using the processing capability of different locations.
- Security
As data is spread across multiple nodes in a distributed environment, they are more vulnerable to unauthorized access or breaches. To prevent this scenario, distributed databases implement robust security mechanisms such as encryption at rest and in transit, access control, and authentication to protect the data.
What is a Distributed Database Management System(DDBMS)?
DDBMS or Distributed Database Management System is software that is used to manage a distributed database running at each node.
This database management system helps to coordinate the different database instances as if they exist in the same physical location. It also helps to synchronize the data-related activity that happens in these databases and makes sure that update done in one database is reflected in all the databases that are located in different locations.
Types of Distributed Databases
We can categorize distributed databases into two architectures.
Homogeneous Databases
In homogeneous databases, there is an availability of consistent resources, operating systems, data structure, and management software across all the sites. All the physical nodes store the databases identically in this architecture. In this type of category, deployment, and management of the database are easier.
Heterogeneous Databases
In Heterogeneous based architecture, different physical sites can have different schema, data models, resources, operating systems, or management software. There is a need for different communication protocols and translations between different sites, as they might not be aware pg each other. This architecture needs a proper translation for query processing and transactions.
Real-world examples of Distributed Database
There are many distributed databases in the market. Following are some of them.
- Apache Ignite
- Apache HBase
- Apache Cassandra
- Amazon SimpleDB
- MySQL
- CockroachDB
- MongoDB
- Apache CouchDB
- Yugabyte DB
Companies using a Distributed database
A distributed database is used by most global IT companies. Some examples are given below.
- Netflix
- Uber
- Airbnb
- Microsoft
- Amazon