What it is, why you need it, and best practices. This guide provides definitions and practical advice to help you understand and manage database replication.
Database replication refers to the process of copying data from a primary database to one or more replica databases in order to improve data accessibility and system fault-tolerance and reliability. Database replication is typically an ongoing process which occurs in real time as data is created, updated, or deleted in the primary database but it can also occur as one-time or scheduled batch projects.
Your organization may have a wide variety of heterogeneous databases, data warehouses, and big data platforms. And, your organization might be spread out geographically, have multiple departments wanting access to the same dataset, or you may have complex data issues like storing data across on premises, cloud, and hybrid multicloud.
Data replication moves your data efficiently and securely across your data integration system. This helps you to improve the performance and availability of your databases and the applications that depend on them, to incorporate new technologies into your IT infrastructure, and to enable data analytics on non-production systems.
Below are the key benefits of replicating databases for your organization.
As with most data integration initiatives, your main challenges here involve managing your finite resources of bandwidth, budget, and time. Synchronizing data across your system requires processes which can add traffic to your network, require higher storage and processing expense, and demand ongoing effort to implement and manage.
Beyond those standard resource constraints, your challenges in replicating databases will typically relate to a poorly defined or managed data governance framework.
Also, handling real-time change streams is quite complex and we address this in the CDC section below.
Learn how to modernize your data and analytics environment with scalable, efficient and real-time data replication that does not impact production systems.
At the highest level, you can distinguish between one-time projects or an ongoing process. Typically, replicating databases is ongoing and data must be copied frequently enough such that changes in one database are updated across the system.
The three most common techniques are full, incremental, and log-based replication. Each scheme has its own advantages and disadvantages but each ultimately involves balancing the competing needs of data consistency and system performance. The right choice for you will primarily depend on your purpose for the replicated data, the amount of data, and how your data is stored.
1) Full table replication copies all existing, new, and updated data from the primary database to the target, or even to every site in your distributed system.
2) Key-based incremental replication identifies updated and new data using a replication key column in the primary database and only updates data in the replica databases which has changed since the last update. This key is typically a timestamp, datestamp, or an integer.
3) Log-based incremental replication copies data based on the database binary log file, which provides information on changes to the primary database such as inserts, updates, and deletes. Most database vendors support this technique (MySQL, PostgreSQL, Oracle and MongoDB) and, assuming that your primary database structure is relatively static, it’s the most efficient of these three types.
As stated above, replicating databases in a low-impact way while trying to reliably handle real-time change streams is quite complex. Below are the four main options to process captured data changes:
Database replication and database backup (also known as mirroring) are often confused but they are not the same process. Mirroring is a form of data replication whereby you maintain a full database backup as a safety precaution in the event of failure in your primary database. As described above, replication involves database objects and the main goal is typically operational efficiency and higher data availability.
You can choose to rely on database replication software provided by your database vendor or you can select a third-party database replication tool. The main advantages of top third-party tools are flexibility and efficiencies. These tools are database-agnostic which means you can use them to copy data across multiple types of databases in your ecosystem.
Modern data integration delivers real-time, analytics-ready and actionable data to any analytics environment, from Qlik to Tableau, Power BI and beyond.