Synapse Analytics Review
Overall Satisfaction with Azure Synapse Analytics
We use it as a primary driver of our DWH solution. We use the spark cluster to process a very large amount of data on a daily schedule. Using Synapse notebooks has enabled us to reuse a single notebook for historization of the data across multiple sources. All of the sources that land in our S3 bucket(either via push or pull mechanism) we are able to clean, store and transform using Synapse notebooks.
Pros
- Large batch load processing
- Reusing notebooks across multiple sources
- Accepting parameters sent from ADF(seamless integration)
Cons
- Its not being actively developed, so no new features
- It lags behind Databricks in features it provides
- Synapse Orchestrator is not the best(Azure Synapse Pipelines)
- Migrating away from legacy database DWH(SQL Server, Oracle)
- Incorporating Delta tables technology
- Lower storage costs(Azure storage is cheaper than storing in a database)
- Much faster processing time(from 12 hours loads to 5 hours)
- Azure Databricks
- Microsoft Fabric
Databricks is a complete product with new features constantly coming out. This can be both good or bad, with a lot of innovation comes a responsibility to keep your code and pipelines fresh.
Fabric on the other hand is a half complete product with a lot of potential, but its yet to be seen if it can be a good competitor to Databricks.
Do you think Azure Synapse Analytics delivers good value for the price?
Yes
Are you happy with Azure Synapse Analytics's feature set?
No
Did Azure Synapse Analytics live up to sales and marketing promises?
I wasn't involved with the selection/purchase process
Did implementation of Azure Synapse Analytics go as expected?
Yes
Would you buy Azure Synapse Analytics again?
No

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