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Dextrus Solution

Data streaming

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What is Real-Time Replication or Streaming of data?

Streaming or real-time replication process, transfers the data as it is created or changed in the source systems to flow through data pipeline and lands and gets merged with or appended to the data in the target platform, allowing businesses to have insights faster on the latest transactions thru the analytical solution. This process, in fact, drives the business to look at the latest trends in more of proactive manner to take informed decisions.

Why should IT organizations choose The Process of Real-Time Replication
The way businesses operate is continuously changing and as the world is becoming a global village, importance of data and the size of the data in any organization is growing rapidly every moment as we speak. For Mid to Large IT organizations, the old way of consuming data once or twice a day from the source system will no longer work. Businesses, expanding their presence across the globe and to various geographical regions of the world, it is quite a difficult process for the senior leadership team to get quick insights on the performance of the business, in case, if the transactions are not available for reporting till the next day. Streaming on the other hand gives lot of flexibility to leadership team to have a quicker insight on the real-time data with single click on dashboards to refresh with latest data.
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There are several types of replication processes.
While building and configuring the data pipelines for supporting data streaming, choosing the right replication method is the most important factor. Incorrectly choosing the Replication Method can cause data discrepancies and latency.
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DB Log Based Replication
This is a method in which modifications done to the source records like, updates, inserts and deletes are identified by reading Database’s binary log files. This method automatically detects the changes happen to the table structures in the source platform. When certain records are modified, the complete row is written to the log file as a log message. Dextrus takes the row-based approach and reads the log messages in sequence, meaning in the same order that the log messages were written to the log. Once this pipeline is scheduled to run, it keeps monitoring the db logs and keeps replicating the data to the target databases. So, it is pretty much real-time data replication process.
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CDC Query Based Replication
This is a method in which changed data is captured using the created on and changed on time stamp columns in the source tables. A bookmark timestamp is maintained to store the last extracted timestamp and by configuring the variables on the CDC columns, the next data set that is to be pulled can be identified by comparing the bookmark timestamp value. Once the pipeline is built, it can be scheduled to run it at frequency starting from once every minute. Depending on the expected data volumes for each pull, this latency can be configured properly.
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Key Based Incremental Replication
This is a method in which the new and updated records are identified by using a column called a Replication Key. This Replication Key is usually a timestamp, date-time, or an integer column in the source table. Dextrus stores the max value of the table’s Replication Key Column for every fetch that happens on the source table. When the next fetch of data happens, it compares the max value of the Replication Key from the previous fetch and all the records that have key value greater or equal to the stored value are replicated and Dextrus stores the new maximum value and this process keeps repeating as long as the replication job keeps running.
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How Dextrus can help IT teams in implementing continuous Data Replication or Streaming
Dextrus comes with several built-in connectors readily available to establish connectivity with ERP systems like SAP ECC, S4HANA, Salesforce etc…and Relational Databases, JDBC connectivity enabled systems, Modern Cloud data platforms, REST APIs, Social Media Platforms like Twitter and many more. Debezium, Confluent Kafka, Delta Lake are few of the important components that are integral part of robust and resilient architecture of Dextrus. May it be DB log based replication, CDC Query based replication or Key Based Incremental Replication, Dextrus has the suitable solutions to accommodate, based on the client’s choice of replication methods.
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