Qlik Replicate to the rescue for Change Data Captures
November 06, 2021

Qlik Replicate to the rescue for Change Data Captures

Anonymous | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with Qlik Replicate

Qlik Replicate is being used as a Data Ingestion layer from enterprise applications and source systems like ERP, CRM by directly scanning the backend DB logs on a real-time basis. Qlik Replicate is used specifically by IT for Data Warehousing and BI reporting. It helps resolve not running a batch-based ETL process to ingest the data into the Data Warehouse staging layers avoiding an expensive overhead to manage additional time-bound processes.
  • Data ingestion.
  • Real-time analytics.
  • Replicating/syncing source data (CRUD operations).
  • Faster data delivery.
  • Quick insights.
  • Reduced dependency on support resources.
  • Saved time and money spend on managing additional processes.
Qlik Replicate was more manageable, very intuitive and easy to understand than the other products like Striim. The learning curve is less with Qlik Replicate and the connectors for various sources was easier to plug and play.
Intuitive, easy to manage and good return on investment.

Do you think Qlik Replicate delivers good value for the price?

Yes

Are you happy with Qlik Replicate's feature set?

Yes

Did Qlik Replicate live up to sales and marketing promises?

Yes

Did implementation of Qlik Replicate go as expected?

Yes

Would you buy Qlik Replicate again?

Yes

Qlik Replicate is well suited for building data pipelines to replace ETL processing, this is extremely useful when the source datasets lack identification of change records. Instead of ETL doing a row by row comparison which is more expensive Qlik Replicate does the delta changes by using watermark from the database logs eliminating the need any additional processing for sourcing the data. It is more appropriate where the need arises to ingest the source data as its generated for faster ingestion and analysis (real-time analytics).