Database replication: Definition, types and setup

Database replication: Definition, types and setup

November 15, 2022
November 15, 2022
Database replication: Definition, types and setup
Database replication involves storing copies of a database in different locations. Learn how it works and how to get started.

Database replication is the practice of creating and storing copies of a database. Learn how it works and how to decide on the right setup for your organization.

Modern enterprises have growing workloads from applications that run critical processes and store important pieces of data. However, traditional on-premises servers are often unable to efficiently handle heightened workloads. These inefficiencies can affect your company’s ability to scale processes and perform real-time analytics, transformations and visualizations on your data.

This is where database replication comes in — the process of creating and storing database copies in multiple locations, such as your cloud data warehouse or data lake. You are able to shift workloads and data storage from your database to a cloud environment.

In this article, we will explain what database replication is, how it works and the key benefits it brings to your modern data stack. We will also cover the different types of database replication and how to determine which replication method is right for your company.


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 is an ongoing process. If a user accesses and changes data in the source database, those changes are synced to the replicated databases. This ensures users are always working with the latest and most accurate data.

There are two types of database replication:

  • Active/active replication: Every system can process changes and the databases are synced in all directions. Some preparation is generally required for active/active replication applications to avoid collisions and this setup is generally used for load balancing or high availability scenarios.
  • Read-only replication: Replicated databases only receive changes from the primary database. Users can read but not modify any data. Read-only databases are used for data democratization giving users access to data without the ability to make changes.

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

How is database replication different from data replication?

Data replication refers to the data you’re replicating. It’s what you’re copying over to your data warehouse or data lake. Examples can include structured data like customer information and operational data produced by your organization from various applications.

In some cases, it makes sense to replicate specific types of data. As an example, if you operate a chain of stores, you might replicate data from your transactional database or a CRM application to a cloud destination where it can be analyzed and mined for useful insights.

In contrast, database replication involves making an identical copy of a table in a database or even the whole database. One could say that database replication is always homogeneous — uses the same technologies — whereas data replication can be heterogeneous.

How does database replication work?

Companies enable database replication via change data capture (CDC), a process that identifies and tracks database changes. It provides real-time tracking as new database events and changes occur. Using a change data capture solution, such as Fivetran, any changes made in the database are replicated to the destination in real- or near real-time. This ensures that all users can access copies of the same data.

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.

Replicating multiple copies of your database

Replicating multiple copies of your database can power a high availability environment and ensure your data is always easily accessible. In the event of a natural or technological disaster causing a data center to go offline, users still have access to their data via a database in an unaffected region and are able to resume operations with minimal disruptions.

Lower data latency

If you have a database hosted in North America, users trying to access the data from a region like Europe or Asia may experience delays. High data latency can have a direct impact on their work.

Database replication allows for localized data access to reduce latency and improve data democratization. With databases replicated in multiple locations, users are able to access the database that’s closest to them.

Reduced server load

Network performance can take a hit when capacity on the database server is lower due to significant data storage or CPU processing. With replication from your database to your destination, you can free space on your production database to keep performance levels optimal. Database replication allows for efficient data processing while maintaining integral and accurate historical data for audit or analytics purposes.

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 replicates consistent across all locations can be a challenge. Poor data governance can lead to replicated databases getting out of sync. With poorly built data pipelines and ineffective use of change data capture, your data accuracy and integrity between your source database and destination could falter.

Employees struggling with data inconsistency

Data loss can also occur during replication. This can happen if database objects are incorrectly configured or if the primary key used to verify data integrity is malfunctioning or incorrect. With data loss due to your database replication, the source database and the destination become out of sync and the data is no longer consistent.

Managing multiple servers and destinations

Managing multiple servers and destinations to store data from your database and its replicates requires additional resources. This can be a time-consuming and resource intensive operation and requires an analysis of the value that your database replication provides.

If you’re relying on cloud services for database replication, you also run the risk of vendor lock-in, meaning it may not be easy to switch to a different service later or you may have limited access to query or update your data.

Addressing technical requirements

When initially setting up database replication, you need to assess your hardware and resources to ensure you have enough bandwidth to support your level of data processing. Meeting these technical requirements can require a complex and costly setup to meet your needs.

Types of database replication

There are three main types of database replication: full-table, key-based incremental and log-based incremental. Understanding each will help you choose the right setup.

Full-table replication

Full-table replication copies every piece of data within a table from the database to the cloud destination; this includes new, existing and updated data.

  • Advantages: Because this replicates the entire table, you will always have the correct data set after each sync and can ensure that all inserts, updates and deletes are captured.
  • Disadvantages: This is the least efficient type of database replication and rather resource intensive as you are copying every piece of data within a table whether it has changed or not. This can also lead to a burst load on the source depending on the size and volume of data within the tables.

Key-based incremental replication

Key-based incremental replication is a database replication method that uses a replication key to identify new and updated records based on a timestamp or integer key..

  • Advantages: Key-based incremental replication is an efficient type of database replication as it only replicates updated and inserted rows thus using fewer resources.
  • Disadvantages: Any data that’s hard-deleted from a database won’t be replicated in your destination of choice without a lot of time and effort put into processes that could identify deletes.

Log-based replication

Log-based replication copies changes based on a database’s binary log files — a file that records patterns, activities and operations within a database.

  • Advantages: This type of database replication is the most efficient, as it reads directly from the binary log files and doesn’t compete with other database queries.
  • Disadvantages: Log-based replication is only available for certain databases or you may not have access to your database’s logs if it is hosted by a third-party. Also, setting up log-based replication can be very time-intensive, difficult, and bug-prone if you build it yourself.

Methods of database replication

There are multiple methods for replicating data from your database. The extensive list of database replication methods allows you to determine a method that suits your infrastructure and tech stack.

Log-based change data capture: A binary log reader parses the transaction log directly to determine changes that have been made to the database. This database replication method allows all changes to be captured including inserts, updates, and deletes due to the replication tool or solution having access to the database’s logs.

Trigger-based change data capture: Every insert, update and delete operation not only performs its respective change, but a trigger fires to record the change in a separate change table that can then be replicated to the destination. This is a resource-intensive database replication method and could potentially require significant amounts of storage depending on the frequency of changes.

Timestamp-based change data capture: Changes are extracted via a mark of the most recent extraction time and replicating every item in the database with a timestamp from that point forward. This will replicate inserts and updates but would not know when a row in the database has been deleted.

Difference-based change data capture: This is a brute force comparison of all data within the database and the destination, where a compressed snapshot is used to compare the two systems and identify changes to each. This method captures inserts, updates and deletes but only runs optimally with smaller data sets.

Getting started with database replication

Database replication helps your organization operate more efficiently, as it makes access to critical data and applications more accessible. Follow these steps to properly implement a database replication process in your organization.

Steps to implementing database replication

1. Identify your data source

The first step is to identify your primary data source where data from your organization originates. This could be any kind of database on-premises or in the cloud. Next, determine the destination you’ll replicate the data to. Potential destinations are major cloud data warehouses, data lakes or even another database.

2. Determine the scope of your database replication

The next step is to consider the data you need to replicate from your database.

If you need to replicate an entire database, you should opt for a full-table database replication scheme. This ensures that all of your data is available in your destination. However, if you only need certain aspects of a database replicated (e.g., analytical data), you would select the source tables and columns to only replicate part of your database.

3. Decide on a database replication frequency

How often do you need the data replicated? Synchronous replication allows for simultaneous updates in real-time. This is typically used for transactional applications that require near real-time data updates. It uses more bandwidth, but it keeps data across the network synchronized.

Asynchronous replication means that data is written to the primary database first. Then the data is replicated to the destination in batches anywhere from every few minutes to daily. It is more cost-effective to have the data in your database sync on a scheduled timeframe, but there’s also the risk of data loss if recent changes aren’t properly replicated.

Decide on a database replication frequency that fits your business needs. However, be sure to carefully weigh the pros and cons of each option.

4. Choose a database replication type and method

Decide on your database replication type: full-table, key-based or log-based. The right choice will depend on factors like your source and destination pairing, the amount of data you need to replicate and the resources available for your database replication.

You will then need to determine what method of database replication you will set up: log-based CDC, trigger-based CDC, timestamp-based CDC or difference-based CDC. Each of these methods has their pros and cons and the optimal choice will depend on the database source and destination you have selected as well as your access to the database’s logs and tolerance for soft- vs hard-deletes.

5. Use a database replication tool

Database replication improves the availability of your data by storing it in multiple locations and potentially reducing the load on your source database. To ensure your data is properly replicated, you’ll need to select the right database replication tool for your use case. This will keep your systems running smoothly and ensure you can get the greatest value out of your data.

Fivetran’s automated data movement platform is the ideal tool to solve your database replication needs. Given Fivetran’s comprehensive offering of multiple database replication types and methods, we can replicate even the largest volumes of data from your database.

One such offering is our high-volume replication solution that uses an agent-based approach to read changes directly from a database’s log files to your destination. It supports large volumes of data and minimizes replication latency to ensure your analytics are run with the freshest of data.

Use a database replication tool

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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