Forum Discussion
data loading is very slow from oracle Db using import
HI Anonymous
How many columns are being loaded, and what's the cardinality of your data?
Columns with high cardinality — such as a datetime column where most values are unique — can significantly slow data loading, as they require more memory to encode and compress in Power BI's VertiPaq engine. Additionally, server-side performance plays a key role. If the Oracle server has limited resources, network latency, or slow I/O response times, it will also affect the speed at which data is retrieved and loaded.Hi Sergii24 and Sergii24 , thanks for your time with such thoughtful response. Really appreciate the way you both broke it down.
Anonymous , just to add on to their points, here are a few suggestions that helped in similar situations.
Thanks for the details. A few practical things you can try to speed up the data load.
- Filter During Import (if possible) – Even though you want all 5M rows eventually, try filtering only recent rows (like last 6 months) during development and remove the filter later. It helps reduce the load time while you're building the report.
- Use Native Query – Instead of loading the table directly in Power Query, write a custom SQL query to only pull the columns you need. This reduces overhead and avoids pulling unnecessary metadata.
- Check for Unnecessary Indexes or Triggers – If the Oracle table has any logging or triggers firing on read, it might slow things down. A DBA can help check that.
- Avoid Loading Complex Data Types – Columns like BLOBs, CLOBs, or high-cardinality fields (like timestamps with millisecond precision or GUIDs) are costly in VertiPaq. Try excluding them during import.
- Switch to OLE DB Connector (Optional) – Sometimes, the OLE DB connector performs better than the Oracle client. Worth testing if you're seeing consistently poor load times.
- Monitor Oracle Server Load – Use Oracle tools or ask your DBA to check if the server is bottlenecked during the load (CPU/disk/network).
Let us know how it goes once we identify the bottleneck, we can dig deeper into optimizations.
Regards,
Akhil.
Hi Sergii24 and Sergii24 , thanks for your time with such thoughtful response. Really appreciate the way you both broke it down.
Anonymous , just to add on to their points, here are a few suggestions that helped in similar situations.
Thanks for the details. A few practical things you can try to speed up the data load.
- Filter During Import (if possible) – Even though you want all 5M rows eventually, try filtering only recent rows (like last 6 months) during development and remove the filter later. It helps reduce the load time while you're building the report.
- Use Native Query – Instead of loading the table directly in Power Query, write a custom SQL query to only pull the columns you need. This reduces overhead and avoids pulling unnecessary metadata.
- Check for Unnecessary Indexes or Triggers – If the Oracle table has any logging or triggers firing on read, it might slow things down. A DBA can help check that.
- Avoid Loading Complex Data Types – Columns like BLOBs, CLOBs, or high-cardinality fields (like timestamps with millisecond precision or GUIDs) are costly in VertiPaq. Try excluding them during import.
- Switch to OLE DB Connector (Optional) – Sometimes, the OLE DB connector performs better than the Oracle client. Worth testing if you're seeing consistently poor load times.
- Monitor Oracle Server Load – Use Oracle tools or ask your DBA to check if the server is bottlenecked during the load (CPU/disk/network).
Let us know how it goes once we identify the bottleneck, we can dig deeper into optimizations.
Regards,
Akhil.