IBM Infosphere: Incremental change log replication to cloud in real time using Apache Hadoop
November 08, 2022

IBM Infosphere: Incremental change log replication to cloud in real time using Apache Hadoop

Fernando Roque | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with IBM InfoSphere Data Replication

IBM InfoSphere Data Replication uses Incremental Data Delivery technology to replicate by reading the native database logs and detecting when a change happens. This is an improved performance alternative to user queries or triggers to see changes and upload the data.IBM InfoSphere Data Replication uploads the data to Apache Hadoop to store the information in clusters. Updates the cloud information in real-time.

Pros

  • Performance to detect changes using Incremental Data Delivery with logs.
  • Update data in the cloud in real time.
  • Saves data in clusters using Apache Hadoop

Cons

  • Better documentation and examples of Console and API.
  • Integration with machine learning to analyze the data.
  • Examples of how to replicate data from multiple sources and databases to one data lake.
  • Incremental Data Delivery for replication. Logs instead of queries to database.
  • Real-time replicaiton to the cloud.
  • Store data in clusters using Apache Hadoop. The clusters improves the performace.
  • Analize the daily data in real time using data lakes and Machine Learning.
  • Performance of the replication without affecting the relational database of the applications.
  • Use of Apache Hadoop for data clustering improving performance.

Do you think IBM Data Replication delivers good value for the price?

Yes

Are you happy with IBM Data Replication's feature set?

Yes

Did IBM Data Replication live up to sales and marketing promises?

Yes

Did implementation of IBM Data Replication go as expected?

Yes

Would you buy IBM Data Replication again?

Yes

IBM InfoSphere Data Replication replication allows work on the daily operation and analyzes the replicated data in real-time with no downgrade of performance. This happens thanks to the incremental data load using the log files instead of querying the database for any changes. It serves as an online backup of the database uploading the data to the cloud in real-time.

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