We were using batch data from an Oracle database, which was causing the Oracle database to slow down. We enabled change data capture and used Striim to read data from Oracle databases and ingest into Snowflake, which was our data warehouse. We were using an ETL model using QlikView, which was taking several days for any software update. With Striim, that has come down to a few minutes. Whenever we do any releases, it would only take a few minutes for Striim to ingest into Snowflake. I would say we went from several days to maybe one to two hours for any release.
I use Striim to perform change data capture from relational databases to non-relational databases in my organization. I implement CDC with Striim by transferring data from Oracle Database to MongoDB in my environment. I have a series of monitored tables where every time a change occurs in the source database, the data is transferred to the target database. The synchronization process is straightforward and efficient for my daily data flows.
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We were using batch data from an Oracle database, which was causing the Oracle database to slow down. We enabled change data capture and used Striim to read data from Oracle databases and ingest into Snowflake, which was our data warehouse. We were using an ETL model using QlikView, which was taking several days for any software update. With Striim, that has come down to a few minutes. Whenever we do any releases, it would only take a few minutes for Striim to ingest into Snowflake. I would say we went from several days to maybe one to two hours for any release.
I use Striim to perform change data capture from relational databases to non-relational databases in my organization. I implement CDC with Striim by transferring data from Oracle Database to MongoDB in my environment. I have a series of monitored tables where every time a change occurs in the source database, the data is transferred to the target database. The synchronization process is straightforward and efficient for my daily data flows.