How can you replicate and synchronize data from external sources for data acquisition in Data Engineering?

1 Data replication methods

Data replication is the process of copying data from one location to another, typically for backup, disaster recovery, or analytics purposes. Depending on the type and volume of data, the network bandwidth, and the desired consistency level, there are various methods of data replication. For example, full replication copies the entire data set from the source to the destination; however, this method may consume a lot of resources and cause data duplication. Incremental replication is another option; it copies only the changes or new data from the source to the destination in real time or near real time. Selective replication is also an option; it copies only a subset of data based on some criteria or filters. This method is flexible but may require a schema or a query to define the subset and avoid data loss.

2 Data synchronization techniques

Data synchronization is the process of ensuring that the data in different locations are consistent and up to date, usually by applying the changes or new data from one location to another. Various techniques exist for data synchronization, depending on the direction and frequency of the data flow, the conflict resolution strategy, and the concurrency control mechanism. For example, one-way synchronization transfers data from one location to another in one direction, usually from the source to the destination. This technique is simple but may cause data inconsistency or overwrite if the destination is modified by other processes or users. On the other hand, two-way synchronization transfers data from one location to another in both directions, usually from the source to the destination and vice versa. This technique is complex but may enable data collaboration or synchronization across multiple locations. Finally, event-driven synchronization transfers data from one location to another based on some triggers or events, usually from the source to the destination when a change or a new data occurs. This technique is dynamic but may require a notification or a listener to detect the triggers or events and initiate the data transfer.

3 Data replication and synchronization tools

Data replication and synchronization tools are software applications or platforms that automate and simplify the process of replicating and synchronizing data from external sources for data acquisition in data engineering. These tools typically provide features such as data connectors to access and extract data from various sources, data transformations to convert and format data into a common schema, structure, or format, data loading to load and store data into a destination, and data monitoring to track and manage the replication and synchronization process. Examples of these tools include Airbyte, an open-source platform that supports over 100 data connectors; Stitch, a cloud-based platform that supports over 150 data connectors; and Fivetran, a cloud-based platform that supports over 200 data connectors. All of these tools allow users to configure and schedule replication and synchronization jobs using a web interface or an API. Airbyte also allows users to create custom connectors using Python or Java . This provides users with the flexibility to tailor their replication and synchronization processes according to their specific needs.

4 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?