If you’re considering how to implement a data replication solution, you’ve likely come across a few different methods of replication. In this article, we’ll look at one common approach: transactional replication.

What is transactional replication?

The basic idea of transactional replication is that it captures and replicates individual object changes – say, to a single row – instead of replicating an entire dataset. A transaction might be changing multiple objects at one time, but it’s key that any change is treated as atomic. To count as a transaction, it will either fail completely or be applied completely.

The definition of transactional replication is perhaps most obvious when compared against snapshot replication. To illustrate: Let’s say you’re replicating a database that tracks reservations at a hotel. Snapshot replication would update the status of every room each time the process was enacted. Transactional replication, though, would only update the rooms that had been reserved or vacated since the previous interval.

Where did transactional replication come from?

Transactional replication, as a term, is a product of Microsoft’s SQL Server terminology. Microsoft originally coined the term to denote replication using a technique called triggers.


Triggers are a typical part of a database offering; the basic idea is that they are automatically executed responses to certain events in a particular table. For example, triggered asynchronous operation allows a user to interact with a database as it’s processing underlying data. The user can do something with the data as it’s being changed, then return control back to the source database so that it can finish processing. Transactional replication initially referred to the use of this capability to transfer change information to another system.

This was useful for replication, but it also created a burden on the source database. And, if the program logic of the trigger logic were to fail, the source database might be left in an unpredictable state that could cause integrity problems.

Because of this, it’s now rarer to use triggers for data replication, but this approach is where the term originated.

How does transactional replication work?

While triggers are still an available method for enacting transactional replication, there are two newer methods that are more commonly used.


The first is for users to embed markers in tables that note every transaction, then use those markers as a key to replicate the data. For example, data replication could use timestamps as a marker, and update any rows where the timestamp had been updated since the previous interval.

One challenge with this approach, though, is that it’s less effective for deleted data; there’s no timestamp when a row is simply gone.


The second (and, usually, best) method of transactional replication is to use log-based change data capture. Log-based transactional replication is the state-of-the-art approach, and it’s what our data replication software, SQDR, uses.

This method takes advantage of the fact that most databases have a log system that allows for forward recovery or the rollback of transactions that weren’t completed. This is a fundamental design principle for reliability in modern databases. Here’s how it works: Changes that are intended to be performed are written to the log first. Those changes are then applied when the update to the log is confirmed.

For data replication purposes, the beauty of this feature is that the integrity of the working database is being maintained in another object outside of the database. So, instead of relying on triggers or tapping the resources of the database, log-based replication can extract any transaction changes from the log itself while the database continues to run unhindered.

What are the benefits of transactional replication?

The main benefit of transactional replication is that it’s better than snapshot replication for real-time accuracy (which is where an entire dataset is moved).

With any replication, there is some latency – a delay between the change and the time it takes to make the changed data available to the consumer. In snapshot replication, there’s more latency; it may even take hours for the process to be completed, depending on the amount of data. Transactional processing systems might only move one element, which can take less than a second.

When should you use transactional replication?

Accordingly, you should generally use transactional replication in environments where real-time fidelity is crucial.

Or, another way of looking at it: You should use transactional replication when the volatility of your data is relatively low. In other words, a large percentage of the whole dataset isn’t likely to be updated in the same interval; instead, each interval will only see a small percentage of data changed. If tracking changes is what’s important and there are only a few changes, you’re essentially concerned with the needle in the haystack. So, when you replicate the data, you should only move the needle, not the whole haystack.

Typically, this works best with systems that represent many individual entries, like bank balances or airplane reservations. Only a fraction of the data is changed in a given interval.

If everything in a dataset is likely to change over a given interval, then snapshot replication often makes more sense.

Ready to implement a transactional replication solution?

Hopefully, the information above has helped you to further understand the process of transactional replication – and its usefulness.

If you’re ready to move forward with a transactional replication solution for your data replication needs, get in touch with us.

At StarQuest, we’re experts at data replication. Our powerful SQDR software can be utilized for replication from an extensive range of data sources, and it powers real-time change data capture using a log-based approach.

And, importantly, our customer service team is regarded as some of the best in the business, with clients calling us “The best vendor support I have ever encountered.”

Get in touch with us to discuss your data replication needs. We can set you up with a no-charge trial of our software using the DBMS of your choice, and help you take the first step toward a solution that will benefit your business.