In this article, we will learn 7 data replication strategies that are used to replicate the data. But first, we will understand why replication of data is important. Data availability is one of the critical challenges today. Many users are frequently accessing the data. Organizations need to speed up the access of the data for the users.
Organizations are using advanced data transfer and data storage systems to optimize data availability. But to follow an organized system of data availability, data replication is the best option.
7 Data Replication Strategies that are best for your business.
Data Replication is a process in which organizations generate multiple copies of the complex datasets and store them in different locations to provide high data availability. There are two types of storage in data replication. The Master storage area holds the original data. Whereas, the Snapshot storage area holds a copy of the datasets from the master storage. The snapshot storage uses the same concept to copy the data from one database to another. However, users from the various locations can access the data seamlessly from their nearest snapshot storage location.
Today organizations are facing many technical issues like server malfunction, hacking of databases, data loss, etc. If organizations contain only a single copy of the business’s critical data, then it turns out to be risky for the organization if the data is not available due to some technical failure.
Therefore, generating and maintaining multiple copies of the business data is the best way to avoid such data availability risks.
- Users from different locations can access the data from their nearest database containing the replica of the data. Therefore, It provides high data availability for users.
- Replication reduces the cost required for maintaining the main data and the cost required for the bandwidth to provide data to multiple users.
- It boosts the availability of the data.
- Data Replication also provides a disaster recovery system to avoid data loss and unavailability.
- Organizations can set up business intelligence processes with the help of data replications.
Based on the security of the data we divide Data Replication into three different types. Here are the following data replication schemes.
In this Scheme, the organization replicates the whole database at each server available on the distributed system. Data availability will improve and the organizations can continue to operate until the last server is active.
Advantages of Full Replication
- Data availability is high
- Organizations can retrieve global queries from any local servers. Therefore, it improves performance.
- It can execute the queries faster due to the high availability of the data.
Disadvantages of Full Replication
- In full replication, scheme concurrency is difficult to achieve.
- To keep all the copies consistent, organizations need to perform a single update on all the databases. Therefore, it slows the updation process.
In No Replication, the replication of the data does not take place. However, each fragment of data is stored in only one master database.
Advantages of No Replication
- Recovery of data is easier.
- Organizations achieve data concurrency because we do not create any replication of the data.
Disadvantages of No Replication
- It slows the process of execution of queries, as multiple users are trying to access the same database.
- The availability of data is low as there is only a single copy of data available.
In Partial Replication, some selective data from the database is replicated. For instance, organizations replicate the data into all the servers available on the distributed system.
Advantages of Partial Replication
- Replication is done considering the importance of the data.
- All the database servers available on the distributed system contain a consistent copy of the data.
- Data Replication can increase the availability of the data.
- It also increases the reliability of the data.
- Improve the performance and supports multiple users.
- Organizations can execute the queries faster.
- To store the replicas of the data organization will require more storage spaces at different locations.
- Replication of data becomes expensive as all the replicas need to be updated.
- The organization will require complex systems to maintain the consistency of data at all the different servers.
There are 7 different data replication strategies based on the process and time the data requires to load from source to replica. For instance, If there is an application whose database requires frequent updates, we can apply the strategy that can take less time for data replication.
Here are 7 Data Replication Strategies that can be used depending on the importance of the data.
Transaction logs are the logs that store the information of the process of the data. These logs come in handy for many reasons like data recovery and identifying the changes made in the source of the data. However, there are some databases that allow users to store the log transaction.
With the help of log transactions, this strategy will identify the update made in the source data, and then the same changes will be updated on the replicated data.
In this replication strategy, the replication of the data is processed with the help of a replication key. In addition, Key-Based Incremental Replication consists of a table in the database. The replication key is one of the columns in the table.
The replication key consists of a value. The tool compares the value stored in the replication key with the maximum value. After that, if there is a difference in both values, the replication tool replicates the data.
We have seen two incremental replication strategies that replicate the data with the help of logs and keys. However, the Full Table replication strategy is completely different from the incremental replication strategy. This strategy replicates the complete database. It replicates every row from source to destination. It does not check whether the data is the same or different, it just replicates the changes made in the source database.
This Replication strategy is simple to use and organizations use this strategy most commonly. For instance, the tool takes a snapshot of the source database and updates the data in the replicated database with the help of the snapshot.
When the tools take a snapshot of the database it cannot track the changes made in the database. For instance, if there is some data that is deleted from the source database before taking the snapshot, the tools cannot identify the deleted data.
To perform a snapshot replication, there are two agents needed to perform the task.
Snapshot Agent: This agent takes all the files and data from the source database and stores them in the same order.
Distribution Agent: This agent is responsible for delivering the files and data to the replicated database.
This Strategy is similar to the snapshot replication. We need to replicate the entire database at first. After that, if any changes are made in the source database, the same is immediately updated in the replicated database.
To verify whether the entire database is replicated or not. The tool takes a snapshot of the source database. There are three agents in this tool that performs the replication strategy.
Snapshot Agent: It performs the same function as the snapshot replication. It collects all the files and data from the source database.
Log Reader Agent: It verifies the log transactions in the source database and updates the change accordingly in the replicated database.
Distribution Agent: It delivers the files and data collected by the snapshot agent to the replicated database.
In this replication strategy, more than one database combines as one database. Therefore, the changes made in the first database reflects in other databases. The process is that when the secondary database receives updates it goes offline updates the changes and sync with the main database and comes back online.
The main advantage of this database is that every database that is used in merge replication can update the data. For instance, if there is some technical issue with one of the databases then you can operate the data from the secondary database.
This replication works similarly to the transactional replication strategy. The source and replica database swap the updates but to swap the update both the databases must be active to perform the updating process.
Every database replication strategy is important in its own way. However, depending on the importance of the data, organizations need to choose the replication strategy. Replication of data also keeps the data safe. There are many applications that support fast and simple data replication tools. In conclusion, the main purpose of data replication is to improve the availability of the data across all the locations.