What Is Database Replication: Tools, Types, & Uses

Ensuring your data assets are always accessible and reliable is critical for your organization's continued operation. However, storing data in a single location can make you vulnerable, as a disruption at that site can significantly impact your business. It emphasizes the need to create multiple copies of your databases across different locations—database replication.    

This article delves into various aspects of database replication, including its types, techniques, and benefits. It also explores several tools that can help you make this process effortless and enable your organization to function normally, even in case of technical glitches.  

What Is Database Replication?

Database replication involves frequently creating electronic copies of a primary database across different locations or servers to ensure data accessibility, fault tolerance, and reliability. These replicas can be located within your organization or other geographic locations, establishing a distributed database system. 

With database replication, you can facilitate continued data availability by providing multiple access points to the same information, even during hardware failures or disasters. This process typically occurs in real-time as you create, update, or delete data in the primary database, but you can also execute it in scheduled batch operations.

Types of Database Replication

You can categorize database replication types based on the method and frequency of data transfer. Understanding these variations is crucial for selecting the optimal approach for your organization's specific use cases.

Asynchronous Replication

Asynchronous replication enables you to copy the data changes made in the primary database to secondary databases with a delay. This approach offers higher performance and scalability but introduces the possibility of data inconsistencies between the primary and secondary databases due to replication lag. You can use this type of replication in analytics and reporting.

Synchronous Replication

Synchronous replication allows you to immediately copy all changes made in the primary database to all replicas before the transaction is considered complete. While this guarantees data integrity, it can introduce some latency. You can use this method in applications demanding high data consistency and availability, such as online banking systems and social networks.

Full Replication

Full replication involves copying the entire contents of a table from a source to one or more target databases. This approach facilitates the propagation of all source data changes, including inserts, updates, and deletions to the replicas. While full replication offers high consistency, it can be computationally expensive due to high-volume data transfers. However, it is crucial during initial data synchronizations. 

Partial Replication

Partial replication empowers you to strategically replicate only specific portions of your database across multiple servers. This approach optimizes resource utilization and reduces storage costs by promoting data deduplication and ensuring critical data availability. Partial replication’s architecture provides you with the benefits of both full and no replication schemes.

Incremental Replication

With incremental replication, you can efficiently transfer only new or updated data from a source database to a target system. This approach minimizes data movement, processing, and storage requirements, making it ideal for large datasets with relatively few changes. It is a comparatively faster replication method and can be helpful in data archiving. 

Techniques to Replicate a Database

Replication of databases allows you to employ various techniques to sync your data across multiple systems. These methods dictate how you capture and propagate data changes to replica databases. Here are three database replication techniques for you to explore:

Log-Based Replication

Log-based replication enables you to efficiently capture and replicate data changes by directly reading a database's transaction log. This method avoids the overhead of tracking individual data modifications, making it faster, high-performing, and less resource-intensive. Popular database vendors like MySQL, PostgreSQL, and Oracle support log-based replication.

Trigger-Based Replication

Trigger-based replication helps you capture database changes using triggers added to the source tables. It ensures all changes directly relate to user actions on the system. This technique allows you to maintain transactional consistency and reduce data loss risk if you scale the database properly. However, trigger-based replication requires modifying existing tables, which may affect the overall performance.

Row-Based Replication

Row-based replication is a hybrid approach that uses a different log instead of the internal Write-Ahead Log (WAL) for replication. This log contains sufficient information to uniquely identify rows and the changes made to them, allowing for data replication across different database versions. You can leverage row-based replication to upgrade database versions with zero downtime.

Advantages of Database Replication

Creating multiple identical copies of your data across different locations can significantly enhance your organization’s data management capabilities. Here are several advantages of implementing database replication: 

• Improved Performance and Reduced Downtime: You can leverage database replication and distribute data across multiple servers to enhance system responsiveness and minimize downtime. If one server fails, others can seamlessly take over, ensuring uninterrupted access to critical data.‍
• Reduced Server Load: Distributing your databases across multiple servers alleviates the burden on individual systems. This improves query performance, responsiveness, and overall system efficiency.‍
• Enhanced Disaster Recovery: By maintaining database copies in different geographic locations, you can significantly reduce the risk of data loss due to natural disasters, cyber-attacks, or hardware failures. This also enables quick recovery and minimal business disruption.‍
• Data Integrity and Consistency: Replication mechanisms help you maintain data consistency across all replicas, ensuring access to reliable and accurate information. By performing regular data synchronization, you can ensure all your databases reflect the latest changes, reducing the risk of data discrepancies.‍
• Scalability: Replication allows you to scale your database infrastructure easily by adding or removing replicas based on your evolving business needs. It helps accommodate changes in data volume or workload seamlessly.

Database Backup vs. Replication

Database backup and replication are both data protection strategies but serve different purposes. In database backup, you create copies of data at specific intervals for recovery in case of data loss or corruption. It is ideal for long-term data retention and compliance. 

On the other hand, database replication involves creating near-real-time copies of data across multiple locations for business continuity. It prioritizes minimal downtime and immediate access to data in case of a primary site failure.

While backup is essential for restoring your data to its previous state, replication ensures uninterrupted operations by providing you with an up-to-date copy of your data.

Use of CDC in Database Replication

Change Data Capture (CDC) allows you to identify and track data modifications in real time, providing a more efficient and scalable approach to database replication. You can employ CDC to handle evolving data streams effectively with minimal impact on system performance. 

Here are several ways you can use CDC to process the captured data changes:

• With transactional CDC, you can mirror the exact order of transactions from the source database, ensuring strict referential integrity and low latency.
• You can implement a data warehouse ingest-merge to leverage native APIs for Snowflake and Azure Synapse and parallel processing of other EDWs for optimized loading.‍
• Batch-optimized CDC allows you to group transactions into batches for streamlining data ingestion and merging for on-premises and cloud targets.
• Using message-encoded CDC, you can capture data changes as messages and stream them to message brokers like Apache Kafka, enabling flexible consumption and processing by various downstream systems.

Database Replication Tools to Ease up the Process

Various replication tools are available in the market, offering multiple features and capabilities to automate and simplify this process. Some popular tools include:

• Database Native Tools: Many modern database systems, such as MySQL, PostgreSQL, and SQL Server, offer built-in features like master-slave replication for creating and managing database replicas.‍
• ETL and Data Integration Tools: While primarily designed for data synchronization, extraction, transformation, and loading, these tools can also handle replication tasks. Airbyte, Microsoft SSIS, and Informatica are a few examples.‍
• Dedicated Replication Tools: You can utilize specialized tools like GoldenGate and Attunity Replicate to implement efficient and reliable database replication. These tools offer features like real-time replication, data compression, and automated failover.‍
• Cloud-Based Services: Cloud providers like AWS and Azure provide managed replication services for seamless data movement between on-premises and cloud environments.

Best Practices to Follow While Replicating Databases

Implementing robust database replication requires careful planning and execution. By adhering to these best practices, you can maximize the benefits of the replication process.

• Define Your Replication Scope: Accurately determine the extent of data you want to replicate by considering factors such as data volume, update frequency, and business requirements. This will help optimize replication strategies and resource allocation.‍
• Choose an Appropriate Replication Method: Consider your source-destination pair, access permission to databases’ logs, and other data characteristics to select a replication method that suits your needs and data infrastructure. ‍
• Plan for Disaster Recovery: Incorporate automatic failover capabilities to ensure quick recovery in case of hardware failure. This enhances your system’s resilience and allows you to run applications seamlessly, even during unexpected disruptions.‍
• Monitor and Optimize Replication Performance: Regularly monitor the performance and status of your replicas. You can leverage tools that provide insights into replication latency, throughput, and potential bottlenecks to resolve problems proactively.‍
• Implement Security Measures: Protect your data during replication using secure data encryptions. This helps guard against unauthorized access or cyber-attacks and ensures compliance with data privacy regulations.

Easiest Way to Replicate a Database with Airbyte

Airbyte is a no-code data integration and replication tool that allows you to establish smooth data movement from disparate data sources to your preferred destination. It facilitates a catalog of over 300 pre-built connectors and a low-code Connector Development Kit (CDK) to help you address all your custom connector needs for streamlined data replication. 

Airbyte offers versatile replication capabilities, enabling you to transfer data in scheduled batches or on-demand. It also provides automation, version control, and monitoring features, enhancing your data replication process. 

Some other features of Airbyte that can make your data replication process more accessible include: 

• Schema Change Management: You can leverage the schema change management feature to configure settings to detect and propagate schema changes occurring at the source. Based on these settings, Airbyte will automatically sync or ignore those changes.‍
• Change Data Capture: Airbyte’s Change Data Capture (CDC) functionality lets you capture incremental changes occurring in the source system and reflect them in the target database. This feature helps you efficiently utilize resources while dealing with constantly changing large datasets.‍
• Versatile Options for Data Pipeline Management: You can easily create your data replication pipelines using Airbyte’s user-friendly interface, APIs, Terraform Provider, and a Python library, PyAirbyte. 
• ‍Enhanced Security: Airbyte provides data security and governance across all deployment models—self-managed, cloud-based, and hybrid. It employs data encryption and abides by industry standards and regulations, including ISO 27001, SOC 2, GDPR, and HIPAA. 

Suppose you want to perform PostgreSQL to Oracle database replication. With Airbyte, you can build your data replication pipeline in just three simple steps:

Step 1: Set up your data source as PostgreSQL.

Step 2: Set up your destination as an Oracle database.

Step 3: Set up a connection between the sources and destination databases.  

You can refer to the official documentation to learn more about Airbyte’s features. 

Key Takeaways

Database replication empowers you to protect your data while maintaining high accessibility, availability, and resilience to security breaches. Based on your scope and requirements, you can implement various database replication types and techniques, including log-based, CDC, synchronous, and row-based replications. This article also introduces tools like Airbyte, SSIS, and MySQL to help reduce downtime and streamline your data processes, leading to sustainable business growth. 

FAQs

What is the data replication process?

Data replication is the process of creating multiple copies of your data across different locations to enhance data availability, reliability, and accessibility within your organization.

Why do we need database replication?

You can use the replicas created during database replication as backups to ensure disaster recovery during unforeseen incidents, such as cyber-attacks or system malfunctions.  

When to replicate a database?

You should replicate a database when your priorities include load balancing, low latency, and data distribution across various geographical regions. 

What is an example of database replication?

An example of database replication is creating copies of a banking database across multiple data centers to ensure continuous service in case of primary site failure.

Is database replication real-time?

Database replication can be real-time or scheduled, depending on the replication method you implement and your specific requirements.

How do data types impact database replication?

Data types influence your database replication’s performance. Efficient data types improve replication speed, while complex data types might require additional processing and resources.