Azure Analysis Services vs. Azure Synapse Analytics

We would have many technical issues and glitches with previous similar providers but found that Azure Analysis Services can simply handle our workload and memory better. I remember we lost an account due to cloud issues not fully saving or corrupting some files. Granted, this is rare with any cloud but haven't had that issue with the same load of memory with Azure Analysis Services.

Incentivized

It's well suited for large, fastly growing, and frequently changing data warehouses (e.g., in startups). It's also suited for companies that want a single, relatively easy-to-use, centralized cloud service for all their data needs. Larger, more structured organizations could still benefit from this service by using Synapse Dedicated SQL Pools, knowing that costs will be much higher than other solutions. I think this product is not suited for smaller, simpler workloads (where an Azure SQL Database and a Data Factory could be enough) or very large scenarios, where it may be better to build custom infrastructure.

Incentivized

• Providing role based access or we can say privilege based on the role to the user if it is integrated with Azure active directory and hence securing the access to sensitive data.
• We use to run different type of analytics services to get the better result which is hectic if done manually or with human efforts.
• We also use to collect bulk of data with the help of this tool and run customized test cases for better efficiency of result and better decision making. The result are very crucial and helps in taking big decision.
• It supports different or we can say heterogeneous database vendors like the Oracle, SQL, and hence make the task easy.

Incentivized

• Create data pipelines to connect with multiple data workspace(s) and external data
• Ability to connect with Azure Data Lake (sequentially) for data warehousing
• Being able to manage connections and create integration runtimes (for onPrem data capture)

Incentivized

• There is very least content available on Microsoft docs and the Internet to get through with AAS.
• i faced lots of connection issues while implementation.
• The need for serious platform experience or expertise.

Incentivized

• It takes some time to setup a proper SQL Datawarehouse architecture. Without proper SSIS/automation scripts, this can be a very daunting task.
• It takes a lot of foresight when designing a Data Warehouse. If not properly designed, it can be very troublesome to use and/or modify later on.
• It takes a lot of effort to maintain. Businesses are continually changing. With that, a full time staff member or more will be required to maintain the SQL Data Warehouse.

Incentivized

The data warehouse portion is very much like old style on-prem SQL server, so most SQL skills one has mastered carry over easily. Azure Data Factory has an easy drag and drop system which allows quick building of pipelines with minimal coding. The Spark portion is the only really complex portion, but if there's an in-house python expert, then the Spark portion is also quiet useable.

Incentivized

Microsoft does its best to support Synapse. More and more articles are being added to the documentation, providing more useful information on best utilizing its features. The examples provided work well for basic knowledge, but more complex examples should be added to further assist in discovering the vast abilities that the system has.

Incentivized

The platform has vast number of features and modules. The UI is sleek and once you get to use to it, you will be able to do a lot of stuff. Also support for data sources is more in Azure Analysis Services.

Incentivized

When client is already having or using Azure then it’s wise to go with Synapse rather than using Snowflake. We got a lot of help from Microsoft consultants and Microsoft partners while implementing our EDW via Synapse and support is easily available via Microsoft resources and blogs. I don’t see that with Snowflake

Incentivized

Basically, the billing is predictable, and this all about it.

Incentivized

• Azure Analysis Service scale resources to match our business needs.
• Helps us to govern, deploy, test and deliver our BI solution with confidence.
• Stores our business data and clients data in a safe place where it's easy to access and visible to all our teams.

Incentivized

• We have had an improvement in our overall processing time
• Cost was much lower than most of its competitors
• Our reporting needs have grown and housing the data here has been great

Incentivized