Data Synchronization: 4 Types & Why It’s Important (2024)

Data synchronization is the process of keeping data consistent and up to date across multiple devices or systems. With successful data synchronization, organizations can be confident that all decision-makers are working with the same—current—information. Without data synchronization, a team may be debating choices informed by inaccurate information, which could feed faulty assumptions that lead to poor outcomes.

The use of cloud data storage has made data synchronization simpler by providing a central, accessible platform for storing and sharing information. But there are still variables to consider.

Data synchronization is different from data integration, though there is a tangential relation between the two. Data integration refers to joining multiple data sources into a single repository for use by various devices and applications such as business intelligence. Data integration focuses on centralization, while data synchronization focuses on a unified view for data consumers. Both processes are about improving data accuracy and utility. When an organization uses both data integration for a central repository and data synchronization for devices, decision-makers get highly accurate and timely information.

There are two ways that data synchronization can be accomplished.

1. Synchronous data updates are sent to all devices that use the data at the same time as these updates are sent to the storage of a primary system that created the data. The goal is that every system instantly sees the same data as soon as it’s created. Examples of synchronous data updates are chat applications, video conferencing, and online gaming. In business, high-end transactional systems synchronously record transactions as they occur.
2. Asynchronous data updates roll out as chunks of data are sent over time, resulting in a slower but more resource-friendly and affordable process. Examples of asynchronous data updates are downloading application updates, receiving emails, or updating data visualizations at semi-regular intervals.

What Is Data Synchronization?

Data synchronization is the process of keeping data consistent among systems, even when it resides in different databases, devices, or storage repositories and is used for different applications. Data synchronization is particularly important when multiple teams or applications need access to the same data and when changes made to that data need to be reflected across all systems in real time. Synchronization efforts work to help ensure data integrity, minimize the risk of data loss or duplication, and help facilitate collaboration and decision-making.

The four main types of data synchronization are as follows:

1. Distributed file systems (DFS): In a distributed file system, files may be stored on any computer within a network. To allow other users and systems to access files, a single name space is created along with appropriate access control systems. If a user ID or application has the appropriate access privileges, it can use a file on a distributed system just as if it were local. The benefit of DFS is that, rather than replicating data, a single authoritative copy can be accessed by anyone on the network. It’s particularly useful for files that are mostly or only read, such as product catalogs. Depending on the scope of the DFS, performance can be an issue.
2. Version control systems (VCS): Version control systems seek to ensure that only one current version of a file exists, while older versions are maintained to show a revision history. At the coarsest level, files are checked out and locked when they are updated and then checked back in when the update is complete. Some systems will allow locking records for update rather than entire files, and still others will show when more than one user is active in a file and record changes so that update histories are maintained. The goal is to avoid the problem of two users or applications updating a file locally and then writing it to an authoritative location, which would cause a conflict.
3. File synchronization: File synchronization updates all known locations of a file when a change has been made to the authoritative version of the file. In the catalog example, local copies may be kept, improving access performance. When changes are made to the primary version, it’s ideal that copies are synced up with the original, but that doesn’t always happen when ad hoc copies are in play. Systems can be designed to allow local copies and to update them as needed. Content delivery networks (CDNs) are a prime example. CDNs distribute and cache huge libraries of content around the internet so that browsing isn’t slowed by reading only the primary copy of an image or video.
4. Mirroring: Also called data mirroring and, rarely, mirror computing. Mirroring is the use of two identical hard drives, with data written to both simultaneously. It is a highly effective although expensive way of managing disk failures. A standard called RAID (redundant array of independent disks) specifies levels of fault tolerance and uses various strategies to allow for drive failures within an array. Mirroring is also known as RAID Level 1. Other strategies use larger sets of drives along with mathematical checksums across drives to achieve the same fault tolerance. The concept of mirroring is used widely in storage systems and can imply anything, including block-level mirroring, file mirroring, drive mirroring, and even storage system mirroring.

Data synchronization delivers business benefits. Having all employees work with the most up-to-date data leads to better decision-making and fewer errors. Additionally, data synchronization allows for better collaboration among teams and improves customer experiences by placing accurate and consistent data across all touchpoints.

Data Synchronization FAQs

How does data synchronization work?

Data synchronization works by updating data stores across a variety of devices so that they contain the same data. With data synchronization, updates occur automatically, either as new data becomes available or on a regularly scheduled cadence. Examples of data synchronization include updating inventory information or product catalogs across systems that need that data.

Why is data synchronization important?

Data synchronization is important because it seeks to ensure that all systems use the latest, most accurate information. It can help facilitate productive collaboration and communication among different teams and departments, reduce the chances of errors from discrepancies in data, and contribute to effective backup and data recovery.

What types of data synchronization exist?

Data updates may be synchronous or asynchronous, and implementing systems will typically come with version-control mechanisms. Synchronization may happen at the transaction level; file level; or at lower levels within storage systems, such as at the block level.

What are the benefits of data synchronization?

Data synchronization benefits organizations by helping ensure that applications and stakeholders are working with accurate, up-to-date information. It can contribute to organizational trust because all users can count on the accuracy and timeliness of data.