Azure Synapse Analytics vs. IBM Analytics Engine

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure Synapse Analytics
Score 7.6 out of 10
N/A
Azure Synapse Analytics is described as the former Azure SQL Data Warehouse, evolved, and as a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives users the freedom to query data using either serverless or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.
$4,700
per month 5000 Synapse Commit Units (SCUs)
IBM Analytics Engine
Score 8.8 out of 10
N/A
IBM BigInsights is an analytics and data visualization tool leveraging hadoop.N/A
Pricing
Azure Synapse AnalyticsIBM Analytics Engine
Editions & Modules
Tier 1
$4,700
per month 5,000 Synapse Commit Units (SCUs)
Tier 2
$9,200
per month 10,000 Synapse Commit Units (SCUs)
Tier 3
$21,360
per month 24,000 Synapse Commit Units (SCUs)
Tier 4
$50,400
per month 60,000 Synapse Commit Units (SCUs)
Tier 5
$117,000
per month 150,000 Synapse Commit Units (SCUs)
Tier 6
$259,200
per month 360,000 Synapse Commit Units (SCUs)
No answers on this topic
Offerings
Pricing Offerings
Azure Synapse AnalyticsIBM Analytics Engine
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
Azure Synapse AnalyticsIBM Analytics Engine
Top Pros
Top Cons
Best Alternatives
Azure Synapse AnalyticsIBM Analytics Engine
Small Businesses
Google BigQuery
Google BigQuery
Score 8.6 out of 10

No answers on this topic

Medium-sized Companies
Snowflake
Snowflake
Score 9.0 out of 10
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Enterprises
Snowflake
Snowflake
Score 9.0 out of 10
Azure Data Lake Storage
Azure Data Lake Storage
Score 8.4 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Azure Synapse AnalyticsIBM Analytics Engine
Likelihood to Recommend
8.2
(9 ratings)
9.5
(9 ratings)
Usability
9.6
(2 ratings)
-
(0 ratings)
Support Rating
9.6
(2 ratings)
-
(0 ratings)
Contract Terms and Pricing Model
10.0
(1 ratings)
-
(0 ratings)
User Testimonials
Azure Synapse AnalyticsIBM Analytics Engine
Likelihood to Recommend
Microsoft
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.
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IBM
  • 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.
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Pros
Microsoft
  • 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)
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IBM
  • 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.
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Cons
Microsoft
  • 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.
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IBM
  • 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.
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Usability
Microsoft
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.
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IBM
No answers on this topic
Support Rating
Microsoft
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.
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IBM
No answers on this topic
Alternatives Considered
Microsoft
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
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IBM
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.
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Contract Terms and Pricing Model
Microsoft
Basically, the billing is predictable, and this all about it.
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IBM
No answers on this topic
Return on Investment
Microsoft
  • 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
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IBM
  • 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.
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ScreenShots