One of the biggest challenges that most organizations face today is ensuring high availability and accessibility of data over the complex set of networks they have in place. Having around-the-clock and real-time access to crucial business data can help organizations carry out processes seamlessly and maintain a steady revenue flow. Organizations, thus have a growing need to scale their systems & provide the support for accessing data seamlessly. This is where Data Replication comes in, and this article will help you replicate databases.
Replicating data is one such technique that allows users to access data from numerous sources such as servers, sites, etc. in real-time, thereby tackling the challenge of maintaining high data availability. This article aims at providing you with in-depth knowledge about how to Replicate Databases seamlessly.
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What is Data Replication?
Data replication refers to the process of generating numerous copies of complex datasets and storing them across various locations to facilitate seamless access. It plays a crucial role in ensuring the high availability of data for individual systems and numerous servers.
Data replication makes use of two different types of storage locations, namely master and snapshot storage areas. Data replication follows the same concept as copying data from one database to another, however, it allows all the users to access the same data seamlessly & without any inconsistencies.
Why Do We Need to Replicate Databases?
The following are some of the key reasons that make database replication a significant process:
- Data Reliability & Availability: Data replication helps organizations ensure high data availability by allowing them to access their data even under extraordinary conditions such as server crashes, data breaches, loss, etc. Hence, it plays a vital role in maintaining accessibility and boosting the reliability of your systems.
- System Reliability: With data replication in place, organizations can ensure a smooth operation of their complex business processes, even during unforeseen data losses, disasters, and system breakdowns.
It helps organizations maintain high data availability and accessibility, thereby allowing them to work in parallel with various issues such as server failure, software glitch, or any malware attacks.
- Robust Performance & Reporting: With data available across different locations, organizations can access, process, and analyze data seamlessly to extract crucial actionable insights.
It further helps businesses ensure robust performance by letting them leverage data and make data-backed decisions without querying the primary database.
- Real-time Data Availability: Strategies such as real-time data replication; help organizations replicate and access the updated data even before saving it on their disk. Hence, data replication helps ensure the real-time availability of data even on low bandwidth, thereby allowing organizations to create compelling reports with ease.
- Robust Disaster Recovery: With replication in place, you will always have a robust data recovery mechanism that helps provide you with multiple replicas of your data across numerous locations.
- Enhanced Server Performance: When data is being processed & run on multiple servers instead of one, it makes data access very quick. Moreover, when all data read operations are directed to the replicas, processing cycles on the primary servers are reduced for more resource-exhaustive write operations.
- Enhanced Network Performance: Data replication helps significantly reduce latency by maintaining numerous replicas of your data across a diverse set of locations. It thereby allows users to access data seamlessly and in real-time.
- Test Performance: Maintaining numerous replicas of the data allows users to distribute and synchronize data availability across various test systems with ease. Hence, it lets users boost the performance of their business applications, allowing them to make data-backed decisions with ease.
General Process of Database Replication
Most in-use enterprise-grade databases such as MongoDB, Oracle, PostgreSQL, etc., house the support for replicating data with ease. These databases allow users to copy data, either by leveraging the in-built replication functionalities or using third-party tools to achieve replication. In either case, the general process of replicating data remains identical.
The following process represents the general steps a user needs to carry out to replicate data properly:
- Step 1: The first step of replicating data is identifying your desired data source and the destination system, where you’ll store the replica.
- Step 2: Once you’ve decided on your data source and destination, you need to copy the desired database tables and records from your source database.
- Step 3: The next important step is to fix the frequency of updates, that is how frequently you want to refresh your data.
- Step 4: With the replication frequency now decided, you now need to choose the desired replication mechanism, selecting between Full, Partial, or Log-based.
- Step 5: You can now either develop custom code snippets or use a fully-managed data integration & replication platform such as Hevo Data, to carry out replication.
- Step 6: With the Data replication process happening, you need to keep track of how the data extraction, filtering, transformation, and loading is taking place to ensure data quality and seamless process completion.
Hevo Data, a No-code Data Pipeline, can help you replicate data from 100+ sources swiftly to a database/data warehouse of your choice. Hevo is fully-managed and completely automates the process of monitoring and replicating the changes on the secondary database rather than making the user write the code repeatedly. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.
Hevo provides you with a truly efficient and fully-automated solution to replicate and manage data in real-time and always have analysis-ready data in your desired destination. It allows you to focus on key business needs and perform insightful analysis using BI tools.
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- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a safe & consistent manner with zero data loss.
- Minimal Learning: Hevo, with its interactive UI, is simple for new customers to work on and perform operations.
- Live Monitoring: Hevo allows you to monitor the data flow, so you can check where your data is at a particular point in time.
- Data Transformation: It provides a simple interface to perfect, modify, and enrich the data you want to export.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects schema of incoming data and maps it to the destination schema.
- Completely Managed Platform: Hevo is fully-managed. You need not invest time and effort to maintain or monitor the infrastructure involved in executing codes.
What are the Techniques of Data Replication?
A database can be replicated in a variety of ways. Because they differ in thoroughness, simplicity, and speed, different techniques offer different benefits. The best technique depends on how businesses store data and what the replicated information will be used for.
There are two types of data replication in terms of data transfer timing:
- When data is sent from the client to the model server — the server from which the replicas get data — it is referred to as asynchronous replication. The model server then sends a ping to the client to confirm that the data has been received. Following that, it copies data to replicas at an unspecified or monitored rate.
- When data is copied from the client-server to the model server and then replicated to all replica servers before the client is notified that the data has been replicated, it is referred to as synchronous replication. This method takes longer to verify than the asynchronous method, but it gives you the assurance that all data has been copied before proceeding.
Because asynchronous database replication occurs in the background, it provides flexibility and ease of use. However, because confirmation occurs before the main replication process, there is a higher risk of data loss without the client’s knowledge. Synchronous replication is more rigid and time-consuming, but it is more likely to ensure data replication success. If it hasn’t, the client will be notified, as confirmation comes after the entire process is completed.
What are the Strategies to Set up Database Replication?
There are multiple ways in which you can replicate Databases:
Strategy 1: Using Custom-Code Snippets to Replicate Databases
You can develop robust custom-code snippets to leverage either of the following methods to replicate databases with ease:
Full Table Data Replication
The full table data replication mechanism allows users to Replicate Databases by making a replica of the entire database by copying the existing, new, and updated data from their data source to a destination of their choice.
This method is exceptionally beneficial for users that delete records manually or if their source databases do not have a suitable column for carrying out log-based or key-based replication mechanisms.
Advantages of Replicating Databases using Full Table Data Replication
- Data with a high level of availability.
- Improves query retrieval performance for global queries because the result can be received locally from any local website.
- Queries are executed more quickly.
Disadvantages of Replicating Databases using Full Table Data Replication
- It requires more processing power.
- Generates/Provides larger network loads instead of copying only edited data.
- Cost increases as the number of rows getting copied increases.
This is how you can use full table data replication to replicate Databases.
Key-Based Incremental Data Replication
Numerous prominent databases, sources, and streaming applications such as Snowflake, Oracle, Kafka, etc., use the key-based data replication mechanism that involves leveraging a replication key to identify the new & updated data. The replication key can be an integer-based, timestamp, and datestamp-based column of an existing source table.
To replicate Databases using the key-based data replication mechanism requires users to ensure the following steps:
- While a replication job executes, the “PipelineWise” store will automatically fetch the maximum value of the target table’s replication key column.
- When the next replication job begins executing, the key-based replication mechanism will automatically compare the key values associated with the previous and current replication jobs.
- Replication will occur if the replication key associated with the table is greater than or equal to the stored value.
- You will then have to repeat the same steps until the data replication process is complete.
Key-based data replication is a crucial process when your desired data source does not support log-based data replication. It further does not detect the “SourceKey” deletes.
You can replicate Databases via key-based data replication by using an SQL query as follows:
WHERE replication_key_column >= 'last_saved_maximum_value'
This is how you can use key-based data replication to replicate databases.
Log-Based Data Replication
Log-based data replication allows users to Replicate Databases by monitoring and recording changes such as updates, inserts, deletes, etc., happening on their source database. Log-based replication method is available only for PostgreSQL, MySQL, and MongoDB backend databases because they support log replication.
This is how you can use log-based data replication to replicate databases. These are some of the mechanisms that you can leverage by creating custom-code snippets to start replicating your databases.
Strategy 2: Using Automated Tools to Replicate Databases
Using custom-code snippets to carry out data replication allows you to replicate databases by developing a customized data replication mechanism that supports your unique business and data needs. However, writing robust code that carries out data replication for your databases is no small feat and requires you to have a great deal of technical expertise.
Hence, if you don’t have the technical bandwidth to develop code or require real-time replication of data, leveraging an automated tool can be the right choice for you. There are a diverse set of tools available in the market today that can help you replicate databases. Some of them are as follows:
- Hevo Data
- Carbonite Availability
- NetApp SnapMirror
- IBM Spectrum Protect
You can click here to check our detailed guide on some of the best data replication tools that you can choose from to replicate databases. It will provide you with in-depth knowledge about these tools, their advantages, disadvantages, use case, and pricing to help you make the right choice.
What are the Advantages of Data Replication?
Advantages of Data Replication are:
- To ensure that all database nodes have a consistent copy of the data.
- To expand the amount of data that is available.
- The reliability of data is improved by replicating it.
- Data Replication is a high-performance solution that supports numerous users.
- The databases are merged and slave databases are updated with obsolete or partial data to remove any data redundancy.
- Because replicas are made, there’s a chance that the data will be discovered where the transaction is running, reducing data travel.
- To make query execution more efficient.
What are the Disadvantages of Data Replication?
Disadvantages of Data Replication are:
- More storage space is required since storing clones of the same data across many places takes up more space.
- When all of the replicas at all of the different sites need to be updated, data replication becomes costly.
- Complex steps are required to maintain data uniformity across all websites.
This article teaches you how to Replicate Databases seamlessly & equips you with in-depth knowledge about the process of data replication, its advantages and disadvantages & answers all your queries about it.
It provides a brief introduction of numerous concepts related to it & helps the users understand them better and use them to replicate Databases & recover data in the most efficient way possible. These methods, however, can be challenging especially for a beginner & this is where Hevo saves the day.
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Hevo Data, a No-code Data Pipeline, can help you replicate data in real-time without writing any code. Hevo being a fully-managed system; provides a highly secure automated solution to help perform replication in just a few clicks using its interactive UI.
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