Modern enterprise applications run critical processes that constantly generate high-value data. Ingesting from these apps can affect their performance and uptime — a business risk often not worth taking. Traditional on-premises servers often struggle to efficiently handle these workloads, especially during peak usage. This situation can hinder a company’s ability to scale processes and perform real-time analytics, transformations and visualizations.

By creating and storing copies of a database in multiple locations, such as a cloud data warehouse or data lake, you can shift workloads and data storage from your primary database to a cloud environment.

In this article, we will explore what database replication is, how it works and the key benefits it brings to your modern data stack. We will also discuss the different types of database replication methods and guide you in determining which one is best for your company.

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What is database replication?

Database replication is the process of creating copies of a database and storing them across various on-premises or cloud destinations. It improves data availability and accessibility. Every user connected to the system can access copies of the same (up-to-date) data.

Database replication creates copies of a database and stores them across various on-premises or cloud destinations, making them available for processing, disaster recovery and other uses. Every user connected to the system can access the same up-to-date data copies.

Replication is an ongoing 24/7 process. When a user changes the source database, those changes are synchronized to the replicated databases. This ensures that all users always work with the latest and most accurate data.

Database replication can be configured in various ways to meet different needs:

• Active/Active Replication: Both databases can process data changes and synchronize bidirectionally, ideal for load balancing and high availability.  
• Read-Only Replication: The primary database pushes updates to replicas that are read-only, useful for data democratization and reporting.

Databases can be replicated once, in scheduled batches or continuously.

How is database replication different from data replication?

Data replication (different from “database replication”) refers to the specific data you’re replicating, such as copying it over to your data warehouse or data lake. This can include structured data like customer information and operational data generated by your organization’s various applications. Some databases offer replication as a built-in feature and others require additional software, such as Fivetran, to handle the replication responsibilities.

In some cases, replicating specific types of data makes sense. If you operate a chain of stores, you might need to replicate data from your transactional database or CRM application to a cloud destination for analysis and valuable insights. A transactional replication strategy allows for real-time or near real-time data synchronization to support dynamic business operations and decision-making processes.

Conversely, database replication involves making an identical copy of a table or even the entire database. Database replication is typically homogeneous, using the same technologies, whereas data replication can be heterogeneous, involving different technologies.

How does database replication work?

Companies implement database replication using change data capture (CDC), a sophisticated method that monitors and logs every change made in the source database, including updates, inserts and deletions. The process captures a complete snapshot of all changes, recording each update, insert and deletion. CDC allows you to accurately replicate a database without the need to execute replication-specific queries against the database.

Change data capture (CDC) relies on log files that sequentially record all changes. This approach preserves the order in which changes occur, maintaining data integrity across replicated databases. Additionally, CDC captures every modification made so that no updates are skipped between synchronization intervals.

Real-time tracking is another hallmark of CDC. Tools like Fivetran rapidly replicate database changes, enabling real or near-real-time updates to the target system. This keeps all replicated environments accurately synchronized, allowing users on various platforms to access updated information. Rapid responsiveness enhances applications reliant on timely data for decision-making, especially in sectors like financial services.

CDC minimizes the impact on the source database by operating asynchronously — changes are captured from the logs as they occur.  This method significantly reduces the database server load by avoiding frequent querying for replication purposes. Additionally, CDC can be configured to filter and replicate only relevant data changes, further optimizing the replication process.

Ultimately the CDC approach to database replication enhances the speed of data integration, a key advantage for businesses that aim to optimize operational responsiveness.

What are the benefits of database replication?

Database replication involves storing copies of your database across various databases, data warehouses and data lakes. Here’s how this practice can benefit your company.

Improved disaster recovery

Relying on a single source database leaves your company vulnerable, as any malfunctions or downtime can prevent access to critical data and disrupt your workflows.

By replicating multiple copies of your database to BCP/DR infrastructure, you can create a high-availability environment that ensures your data is always accessible. In the event of a natural or technological disaster causing a data center to go offline, users can still access their data via a database in an unaffected region, allowing operations to continue with minimal disruptions.

Reduced server load

Network performance suffers when capacity on the database server is lowered due to significant data storage or CPU processing. Replicating your database to a destination offloads some of this burden, freeing up space on your production database and keeping system performance levels optimal. This is why CDC should be the default replication process for your databases: significantly reduced load and the replication processes minimize overhead on the application’s infrastructure.

Enhanced data analytics

Database replication boosts analytics by creating an isolated environment for data queries, leaving core system performance unaffected. Analysts can execute complex queries in this replicated setting without slowing down operational systems, gaining real-time access to large datasets. This enables quicker insights and more fluid data exploration

Real-time business intelligence 

Real-time data access across all business units enhances accuracy in reporting and decision-making. BI tools retrieve the latest data without delays, enabling more informed business strategies. Additionally, this approach simplifies the integration of disparate data sources, fostering a more cohesive BI strategy.

Predictive AI/ML applications

AI/ML applications benefit significantly from database replication, as it supplies them with consistent, up-to-date datasets for training models. Having access to a broader datasets enhances the predictive power of models and allows for real-time learning from incoming data. This capability enhances applications that depend on quick data-driven actions, especially those involving personalization algorithms and predictive maintenance systems.

What are the challenges of database replication?

Database replication offers numerous advantages — it improves data availability, lowers latency, reduces server load and safeguards against data loss. However, replicating your databases isn’t without risks.

Here are some of the common challenges of database replication.

Ensuring data consistency

Keeping databases and their data replicas consistent across locations can present challenges. Ineffective data governance may result in databases becoming out of sync. If data pipelines are poorly constructed or can’t effectively manage schema drift, the accuracy and integrity of your data between the source database and its destination may be compromised.

Additionally, data loss can occur during the replication process. This typically happens if database objects are configured incorrectly or if the primary key, which verifies data integrity, is malfunctioning or incorrect. Such incidents of data loss during replication can cause the source database and its destination to fall out of sync, leading to inconsistencies in the data.

Managing multiple servers and destinations

Manually managing data storage across multiple servers and destinations necessitates additional resources, making it both a time-consuming and resource-intensive endeavor that requires assessing the benefits your database replication offers. Yet, relying on cloud services for database replication is also problematic, as it introduces the risk of vendor lock-in. Accepting this limitation can potentially complicate any future changes to services or restrict your ability to query or update your data.

Implementing a Backup Strategy

A robust backup strategy takes into account various critical factors, including the frequency of backups and the types of backups — full, incremental or differential — that best suit the organization's operational needs. It's crucial to choose a suitable storage location for these backups to optimize for cost, performance and compliance with regulatory requirements. 

Additionally, the strategy must ensure data redundancy by using database management systems to manage and automate the replication processes across master and secondary databases. This setup should include replication groups, which involve multiple nodes to ensure consistent data availability and fault tolerance across the system.

To maintain the integrity and reliability of backups, regular testing of data backup processes is essential to ensure they can be restored accurately and promptly. Neglecting this verification step risks serious disruptions to business continuity, which can have grave financial consequences. 

Types of database replication

There are three main types of database replication: full-table, key-based incremental and log-based incremental. Choosing the right type of database replication depends on your specific needs.

Full-table replication

Full-table replication involves copying every data element within a table from the database to the cloud destination, including new, existing and updated data.

• Advantages: Full-table replication ensures you consistently have an accurate dataset after each synchronization. It captures all inserts, updates and deletes, providing complete data integrity and ensuring no transaction is missed.
• Disadvantages: This approach is the least efficient form of database replication and can be quite resource-intensive. Since it involves copying every data element within a table, regardless of whether it has changed or not, this can lead to significant loads on the source database, particularly when dealing with large volumes of data.

Key-based incremental replication

Key-based incremental replication is a database replication method that identifies new and updated records for replication using a key, typically based on a timestamp or integer.

• Advantages: This method of database replication is highly efficient as it only replicates rows that have been updated or newly inserted, thereby using fewer resources and minimizing unnecessary data transfer.
• Disadvantages: A significant drawback of key-based incremental replication is that it does not automatically replicate data that has been hard-deleted from the database. Detecting and replicating deletions require additional time and effort, as it involves more complex processes to identify and handle deleted data effectively.

Log-based replication

Log-based replication involves copying changes from a database’s binary log files — files that record patterns, activities and operations within the database.

• Advantages: The most efficient type of database replication because it directly reads from the binary log files without interfering with other database queries.
• Disadvantages: Log-based replication is only suitable for certain types of databases. Additionally, access to the database’s logs may not be available if the database is hosted by a third-party. Setting up log-based replication can also be time-intensive, challenging and prone to bugs if constructed independently.

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Methods of database replication

There are multiple methods available for replicating data from your database, each suited to different infrastructures and technical stacks.

Log-based change data capture: A binary log reader directly parses the transaction log to identify all changes made to the database, including inserts, updates and deletes. With direct access to the database’s logs, this replication tool ensures a highly efficient process that minimizes the impact on database performance and provides near real-time data replication.

Trigger-based change data capture: In this method, every insert, update and delete operation triggers a recording of the change in a separate change table, which is then replicated to the designated destination. A resource-intensive approach that may require significant storage capacity, especially if changes occur frequently.

Timestamp-based change data capture: Involves capturing changes by marking the most recent extraction time and replicating every item in the database from that timestamp onward. It effectively replicates inserts and updates; however, it does not detect when a row has been deleted from the database.

Difference-based change data capture: Employs a brute force approach by comparing all data between the database and the destination using a compressed snapshot. A snapshot replication allows for the detection of inserts, updates and deletes but is most effective with smaller datasets due to its intensive data comparison requirements. 

Getting started with database replication

Database replication enhances your organization's efficiency by making critical data and applications more readily available. Here are the steps to effectively implement a database replication process in your organization.

1. Identify your data source

Begin by pinpointing your primary data source, where your organization's data originates. This source could be a database located on-premises or in the cloud. Once identified, decide on the destination for replicating the data, which might include major cloud data warehouses, data lakes or another database.

The database you choose to replicate should have a business requirement for doing so. It’s not necessarily a good practice to replicate all your data all the time. Consider your BCP/DR strategy and the actual risk of data being unavailable for some amount of time.

2. Determine the scope of your database replication

Next, assess the data you need to replicate. If the requirement is to replicate an entire database, opt for a full-table replication scheme to ensure all data is available at the destination. For more specific needs, such as replicating only analytical data, choose to replicate selected tables and columns.

3. Decide on a database replication frequency

Consider how frequently you need the data replicated. Synchronous database replication updates data in real-time across the network, suitable for transactional applications that demand up-to-date data. Although synchronous replication uses more bandwidth, it ensures data is continuously synchronized. 

Alternatively, asynchronous database replication writes data to the primary database first, then batches the data to the destination periodically — from a few minutes to daily. This method is more cost-effective and allows for scheduled data synchronization, although it carries a risk of data loss if recent updates are not replicated properly. However, implementing a comprehensive monitoring system before asynchronous replication occurs will capture these changes.

4. Choose a database replication type and method

Select the type of database replication that best suits your needs: full-table, key-based or log-based. The appropriate choice will depend on factors such as the pairing of your source and destination, the volume of data you need to replicate and the resources available for managing your database replication.

Next, determine the specific database replication method you will implement, such as log-based change data capture (CDC), trigger-based CDC, timestamp-based CDC or difference-based CDC. Each method has its advantages and drawbacks and the best choice will depend on the particularities of your database source and destination, your access to the database logs and your requirements for managing soft versus hard deletes.

5. Use a database replication tool

Database replication tools enhance data availability by storing copies in multiple locations and can reduce the load on your source database. To ensure effective replication, it helps to choose the right tool tailored to your specific use case. With numerous database replication tools available, selecting the right one ensures smooth system operations and maximizes the value extracted from your data.

Fivetran offers an automated data movement platform that is highly suitable for a wide range of database replication needs. With Fivetran's extensive range of database replication techniques, the platform can handle even the largest data volumes efficiently. 

One of Fivetran’s solutions includes a high-volume replication solution that uses an agent-based approach, reading changes directly from the database’s log files to minimize latency and ensure that your analytics are performed with the most current data.

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Advanced replication techniques and architectures

Understanding what specialized replication methods exist and how they are implemented in different types of databases can help you choose the right strategy for your specific needs.

1. Replication in SQL and NoSQL environments

• Oracle and Microsoft SQL Server: These platforms use advanced replication techniques to ensure data consistency across multiple locations. Techniques like merge replication and master-slave replication are commonly employed to manage data across distributed environments.
• NoSQL Databases: These databases often handle replication differently to accommodate large amounts of unstructured data, using methods that ensure quick response times and high availability across global systems.

2. Understanding replication topologies

• Partial and multi-node replications: Some scenarios require only part of the database to be replicated, known as partial replication, which is useful for specific applications or reduced resource usage. In contrast, multiple node replication involves several replica servers to enhance data availability and fault tolerance.
• Single database vs. replication groups: A single database setup might be simpler and easier to manage, whereas replication groups involve coordinating changes across multiple databases to ensure consistency and reliability.

3. Specialized use cases

• Model servers and data stores: In settings where real-time data analysis is crucial, such as in predictive modeling or real-time analytics, replication needs to be fast and accurate. This ensures that all nodes in the system are working with the most current data.
• Global data management: For organizations operating worldwide, managing data across different regions can be challenging. Replication strategies must address issues of latency and data integrity to ensure that users worldwide can access consistent and accurate information.

4. Challenges and considerations

• System management and user experience: Managing these complex replication setups requires robust database management systems that can handle everything from conflict resolution to ensuring that the user experience remains unaffected by backend processes.
• Technical and operational challenges: Setting up these systems often involves significant technical expertise and understanding of how different replication methods, like log-based and trigger-based change data capture, work. This knowledge is crucial for maintaining system performance and data accuracy.

By understanding these advanced replication techniques and the architectures in which they operate, organizations can better prepare to implement a database replication strategy that suits their specific operational needs and challenges. This deeper knowledge will also help in troubleshooting and optimizing database replication processes.

Choosing reliable database replication software

Database replication serves multiple purposes: it secures your data against physical and technical failures and also enhances access to real-time data across geographically dispersed teams. Consistent and reliable access to updated data supports efficient decision-making and operational continuity across different regions.

However, database replication isn't just about duplicating data; it can also play a key role in a comprehensive backup strategy. Here are some strategies where replication is vital:

• Disaster recovery planning: Uses replication to create a backup system that exactly mirrors your primary setup. If a system failure occurs, you can switch to the backup with minimal downtime. 
• Data localization: Replicates data across different geographical locations to improve access speeds and comply with local data laws. It's like having a local backup wherever your users are.
• Load balancing: Spreads the workload evenly across several servers. Helps handle traffic more efficiently and ensures that if one server goes down, the other servers will pick up the slack.  
• Archiving: Copying data to a secure storage system for the long haul. It's key for meeting legal storage requirements and keeps a historical record of data for retrieval when needed.

Your replication strategy should fit your organization's unique needs, risks, and operational demands. It should also support recovery and compliance requirements. With this criteria in mind, the right approach can significantly impact your ability to manage high data volumes, guarantee availability, and strengthen disaster recovery measures. 

Embracing advanced replication technologies like those offered by Fivetran can markedly simplify the replication process. Fivetran minimizes the load on your systems while making sure your data is swiftly synchronized. This capability is needed in environments that cannot tolerate high latency or downtime. It offers businesses the assurance that they can operate continuously and efficiently.

In choosing a database replication solution, consider how tools like Fivetran align with your long-term goals to support scalability and robust data governance. The right tool can make database replication less about managing data and more about enhancing business agility and strategic data usage. Explore how leveraging Fivetran technology can redefine your data system’s resilience.

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Improve data availability with high-volume database replication

Looking for a database replication solution? Look no further than Fivetran. Our change data capture solutions let you quickly move large volumes of data with minimal latency and real-time delivery. Couple this with efficient operational ability to switch between database sources and various cloud destinations, and you become unstoppable!

Sign up for a 14-day free trial to learn more about Fivetran’s database replication offerings and discuss your use case further.

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