1. OLTP workload – Azure SQL DW is an MPP database, data is distributed in many servers to improve reads thus it would hurt your OLTP writes.
  2. High volume of small reads and writes – Same as above
  3. Multi-Tenancy Database –  would be a nightmare to restore a single schema in case your environment is compromised, Azure SQL DW does not offer RLS, Always Encrypted and Column Level Encryption (CLE)
  4. Frequent changing of schema
  5. Row by row processing – in a scenario where UDF’s are needed to process data, MPP system would be a disservice to your processes.
  6. JSON, XML data and Spatial, Struct, Array and Map data types
  7. Power BI direct query requiring dashboard performance – with direct query mode Power BI will perform poorly with a large data set in Azure SQL DW
  8. High concurrency of queries (eg. hundreds of thousands of concurrent queries) – currently Azure SQL DW does not have plan caching mechanism thus all queries have to go through plan search space to find an execution plan.
  9. Small datasets (less than 250GB) – it’s an MPP system
  10. Disaster recovery with stringent RPO and RTO – Azure SQL DW does not have the capability to automatically replicate data to another hot/standby Azure SQL DW for DR purpose. Yes, it’s geo-redundant for data replication every 24hrs to other data centers thus there is the possibility of data loss.

9 thoughts on “10 scenarios where Azure SQL DW is not a good fit”

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