Organizations use digital solutions, including APIs, IoT devices, web applications, and mobile applications, to run business operations. However, this leads to data being stored in disparate sources. With multiple data sources, it becomes crucial to connect with each application to maintain harmony and stay updated. That’s where data synchronization comes in.
In this article, we will discuss data synchronization in detail, and you will know its types, ways to synchronize data, benefits, tools, and much more.
Types of Data Synchronization
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There are two types of data synchronization:
One-way Synchronization
One-way or uni-directional synchronization is when the data flow is in a single direction, generally from a data source to a centralized system. In this type of data sync, the changes or updates in the source reflect on the centralized system. However, if you make changes in a centralized system, it won’t replicate in the data source. Usually, one-way synchronization is used when there is only one primary system, the centralized system.
Two-way Synchronization
In two-way or bidirectional synchronization, data flows in both directions, from the data source to the destination and vice versa. This data sync ensures both systems communicate with each other in near-real time, and changes in one are reflected in the other. Two-way sync is mostly used when collaborating with systems or individuals to work with shared data. A general example of this synchronization will be sales and marketing applications. When a sales team generates a lead, it reflects on the marketing platform and vice versa, ensuring real-time collaboration.
How to Synchronize Data?
There are many ways you can use to synchronize data. Your choice should depend on the kind of data and specific business requirements. Below are the ways to perform data synchronization with their use cases:
Native Integrations
Using native integration, you can directly connect two or more applications to synchronize data without relying on third-party tools or applications. It usually works one way, so the integration is classified as data push rather than data synchronization. This method is done with the help of Application Programming Interfaces (APIs), webhooks, or other custom connectors your application uses.
Native integration works great to automate straightforward workflows, and connecting two tools is the only concern. A good example of native integration includes connecting two cloud-based applications within an organization.
Use cases
- Basic Data Transfer: You can use native integration when automating simple workflows like synchronizing the data of the database with the business intelligence tool to perform reporting and analytical operations.
- Near Real-time Updates: This method works well when synchronizing data in near real-time.
Custom Coding
Custom coding includes custom-built applications, services, or systems made by your team for specific data synchronization needs. Unlike native integration, this method can use different third-party tools and technologies to help streamline some tasks and make data synchronization easier. Usually, an organization with unique synchronization requirements uses this method, as it offers flexibility and scalability.
While custom coding can achieve true data synchronization, it is resource-intensive. It requires a dedicated development team and is time-consuming.
Use cases
- Advanced-Data Transformations: Custom coding helps perform complicated data manipulation, aggregation, and filtering in a data transformation task.
- Unique Requirements: Custom coding is frequently chosen by businesses with very specific requirements in data synchronization that other tools cannot address.
Third-Party Integration Platforms
Third-party platforms or integration platforms as a service (iPaaS) can streamline the data synchronization process by automating the most complex tasks. These platforms typically provide a range of applications to implement integrations with very little technical expertise. IPaaS can include:
- Cloud-based storage.
- Cloud data synchronization.
- Execution of integration flows.
- Data management.
- Development.
- Data governance.
It is important to note that many tools provide data synchronization services, each having its use case, services, quality, and cost. Therefore, you need to evaluate your options in detail.
Use Cases
- Reduced Development Overhead: While using third-party tools, you don’t need a dedicated team of developers to synchronize data. Therefore, it reduces the need for extensive development.
- Efficiency: With its rich features and functionalities mentioned above, iPaaS allows you to streamline the integration process between several applications.
Robotic Process Automation (RPA)
RPA is a software or tool that mimics the way humans interact with software to perform repetitive tasks. In data synchronization, RPA tools help automate the task of data replication between applications at the user interface level. However, this method is not widely used as the bots can be error-prone, and small mistakes can break the synchronization process. Just like custom coding, RPA’s require technical expertise to implement and maintain in your system, which makes it resource-intensive. Therefore, while synchronizing data, RPA is useful when a temporary workaround is required or no other integration option is available.
Use Cases
- Automate Human Intervention: RPA offers an automated solution when human intervention is necessary throughout the data transfer procedure.
- Temporary Workarounds: Usually, RPA is used where businesses require an immediate fix for temporary data synchronization barriers.
Benefits of Data Synchronization
Data synchronization offers a lot of benefits for a data-driven organization. Some of them are mentioned below:
Automating Data Collection
Manually inputting data can lead to errors that impact data integrity and accuracy, whether by putting incorrect information or forgetting to input. Data synchronization plays the role of automating data collection by continuously updating the data between applications whenever there is even a slight change. It ensures employees don’t have to do the manual work of re-entering data, which allows them to avoid errors.
Data Quality
Having quality data creates a strong foundation for data management. It allows you to be consistent over different tasks and streamline collaboration. Automated data synchronization ensures information goes through different filters. Therefore, the data quality is carefully monitored so that you can work with top-quality data throughout the organization.
Data Backup
Data backup is the process of creating a copy of your data and storing it in the application or a cloud environment. You may require a data backup in many cases, such as system errors and maintaining system uptime.
Best Tools for Data Synchronization
Choosing the right tool is essential for efficient data synchronization between databases, systems, and applications. Here are some of the best tools for this process:
Hevo is the only real-time ELT No-code Data Pipeline platform that cost-effectively automates data pipelines that are flexible to your needs. With integration with 150+ Data Sources (40+ free sources), we help you not only export data from sources & load data to the destinations but also transform & enrich your data, & make it analysis-ready.
Key features of Hevo:
- Recently, ELT has emerged as a preferred technique for setting data pipelines because of its efficiency. Hevo’s no-code ELT pipeline is a solution that allows you to load huge datasets quickly and provide data access to analysts.
- Hevo provides flexible options for data replication from source to destination. You can choose to replicate the entire database, individual columns,s or specific tables, allowing you to focus only on relevant data.
- Hevo offers a Smart Assist solution built into the product that provides overall visibility and control of your data while minimizing costs. Additionally, it provides alerts on pipeline updates, activation status, or data ingestion through third-party applications or emails.
- Hevo provides full support for recovering from any issues at the source end and keeps retrying until data ingestion is completed efficiently. Similarly, if a destination has issues, it retries the data load to ensure no records are lost.
Apache Nifi
Apache Nifi is an open-source integration tool that specializes in data synchronization. It offers a near real-time data movement facility to manage data movement between multiple sources and destinations.
Key features of Apache Nifi include:
- An easy-to-use interface allows technical and non-technical users to easily build and manage data flows.
- The platform performs well in situations requiring streaming and synchronizing data in near-real time.
- Apache Nifi has many processors and extensions available to customize data format transformation, encryption, aggregation, and more for synchronization.
DryvIQ
DryIQ is known for allowing organizations to migrate and classify data with two-way sync across multiple systems. The platform specializes in synchronizing data across storage platforms and migrating system files at scale.
Key features of DryvIQ include:
- It can synchronize files between on-premise solutions and cloud applications.
- DryvIQ can discover high-risk, sensitive, obsolete, and redundant data.
- It allows you to analyze, migrate, copy, and synchronize content at scale.
Conclusion
Data synchronization is a necessary element in data management. It ensures consistent data flow throughout the organization to maintain data integrity and accuracy and streamline business processes.
Businesses can use SaaS platforms like Hevo to streamline the data synchronization process. It allows you to directly update data changes from a source to a destination in near-real time without having technical expertise.
Want to take Hevo for a ride? Sign Up for a 14-day free trial and simplify your data integration process. Do check out the pricing details to understand which plan fulfills all your business needs.
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Jalaj has over four years of extensive experience in technical writing within the data industry. He is passionate about simplifying the complexities of data integration and data analysis, crafting informative content that aids those delving deeper into these subjects. Through his work, Jalaj aims to make sophisticated data concepts accessible and understandable, empowering readers to enhance their knowledge and skills.
