Everything you need to know about Change Data Capture in SQL

Data is at the core of every business in the modern economy. Data determines the growth trajectory of every business, however small or large. Today, more companies are making decisions based on data analysis, and deriving insights to improve their products, services and core offerings.

One of the key facets to making data-driven decisions is how up-to-date information is available at hand. In a hyper-connected, always-on world, data is continuously flowing around us, and it constantly updates itself. This is why the need for fresh, up-to-date data access is critical to a business’s success.

Despite this being common knowledge, not many companies are able to use relevant data to derive insights. In fact, a study pointed out that about 60% of businesses worldwide make misinformed or slow decisions due to accessing data that is not updated, or of poor quality.

The biggest reason for this is the use of batch processing of data where real-time sync of databases is not possible. Around 75% of global businesses are still reliant on batch processing for data processing, making themselves slow, inefficient and misinformed.

This is where new technologies are emerging to make a major shift in the way businesses make use of data to make decisions. One such solution is Change Data Capture or CDC which enables databases to sync in real-time and deliver more efficiency. With Change Data Capture, businesses can track changes in the source dataset and automatically update and transfer those changes to the target database.

If we compare Batch Processing versus Real-time Change Data Capture, we understand the key differences:

  1. In Batch processing, data is not synced in real-time, whereas Change Data Capture (CDC) enables constant, instantaneous tracking of changes in data.
  2. Batch processing enables data replication only when required resources are available for allocation, whereas CDC immediately updates the target database using stream processing.
  3. In batch processing, if the data queries are too large, it causes latency in the system, and slows down the replication process. On the other hand, Change Data Capture  does not require a constant or periodic basis, which saves the system from load spikes, and does not strain the system.

With CDC, businesses can instantly and incrementally replicate data from multiple sources such as operational databases, applications, ERP mainframes, and other cloud-based platforms such as BigQuery, Snowflake, Microsoft Azure, and Amazon Redshift.

For businesses and developers working with an SQL server, there is a built-in technology function called SQL server CDC, which is used to detect and capture changes made to a database automatically. With SQL CDC, key operations such as insert, update and delete can be instantaneously applied to a database table and then stored for consumption by any application for further use.

So, what are the benefits of using SQL server CDC for data-driven businesses?

  1. Higher Revenue: The use of data depends on its value, and the value of data depends upon its relevance. Businesses that make use of out-of-date, old data stand at the risk of losing customers, and making misinformed decisions.
    There are both short and long term consequences of not having access to real-time data for analysis and insights. Change Data Capture solves this by providing access to fresh, most up-to-date data to businesses, using which they can make actions in real-time, and improve data analysis at the speed of doing business.
  • More Savings: Every time data is updated in a source table, it requires updating in the target system, which requires a minimum bandwidth. Batch processing of data requires massive upfront costs to store and update high volumes of data, and it often leads to load spikes in network traffic, and costly migration from source to target databases.
    Change Data Capture solves this by loading data incrementally, instead of all at once, which requires miniscule bandwidth and causes no congestion in the network traffic. For businesses, this translates into reduced data transfer costs, fewer operational overheads and increased time savings.

The takeaway is this – in a 24/7 work environment, businesses cannot afford to ignore the benefits and upsides of using Change Data Capture (CDC).

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So, if your business is ready to execute SQL server CDC (Change Data Capture) for real-time data replication and analysis, then there are two ways of doing so.

The first option is to manage the installation and implementation of SQL Server change data capture processes and commands on your own, which requires expertise, investment in time, and dedicated resources for coding.

The second alternative is to leverage partners and service providers who can help you replicate your business data through your business data systems and implement real-time data stream change to a cloud warehouse.

If you want to save time, resources, and hassles, you can explore Bryteflow for SQL server CDC which guarantees lightning-fast data replication from source to target and does not require admin access or log-based permissions. With Bryteflow, you can easily load and merge changes in the data without slowing down your servers or systems.

Bryteflow offers a seamless, secure solution to replicate business data without any coding or installation of software or hardware at your end. Experience high-performance SQL server CDC with Bryteflo and harness the power of data for faster business growth.

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