Likelihood to Recommend 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.
Read full review Well suited for my big data related project or a static data set analysis especially for uploading huge dataset to the cluster. But had some issues with connecting IoT real-time data and feeding to Power BI. It might be my understanding please take it as a mere comment rather than a suggestion. Read full review Pros 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) Read full review Jobs with Spark, Hadoop, or Hive queries are rapidly attained Can collect, organize and analyze your data accurately You can customize, for example, Spark or Hadoop configuration settings, or Python, R, Scala, or Java libraries. Read full review Cons 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. Read full review Easier pricing and plug-and-play like you see with AWS and Azure, it would be nice from a budgeting and billing standpoint, as well as better support for the administration. Bundling of the Cloud Object Storage should be included with the Analytics Engine. The inability to add your own Hadoop stack components has made some transfers a little more complex. Read full review Usability 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.
Read full review Support Rating 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.
Read full review Alternatives Considered 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 Read full review We initially wanted to go with
Google BigQuery , mainly for the name recognition. However, the pricing and support structure led us to seek alternatives, which pointed us to IBM.
Apache Spark was also in the running, but here IBM's domination in the industry made the choice a no-brainer. As previously stated, the support received was not quite what we expected, but was adequate.
Read full review Contract Terms and Pricing Model Basically, the billing is predictable, and this all about it.
Read full review Return on Investment 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 Read full review This product has allowed us to gather analytics data across multiple platforms so we can view and analyze the data from different workflows, all in one place. IBM Analytics has allowed us to scale on demand which allows us to capture more and more data, thus increasing our ROI. The convenience of the ability to access and administer the product via multiple interfaces has allowed our administrators to ensure that the application is making a positive ROI for our business users and partners. Read full review ScreenShots