Likelihood to Recommend 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
My recommendation obviously would depend on the application. But I think given the right requirements, IBM DB2 Big SQL is definitely a contender for a database platform. Especially when disparate data and multiple data stores are involved. I like the fact I can use the product to federate my data and make it look like it's all in one place. The engine is high performance and if you desire to use Hadoop, this could be your platform.
Read full review Pros 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 data storage data manipulation data definitions data reliability Read full review Cons 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 Cloud readiness. Ease of implementation. Read full review Usability
IBM DB2 is a solid service but hasn't seen much innovation over the past decade. It gets the job done and supports our IT operations across digital so it is fair.
Read full review Support Rating
IBM did a good job of supporting us during our evaluation and proof of concept. They were able to provide all necessary guidance, answer questions, help us architect it, etc. We were pleased with the support provided by the vendor. I will caveat and say this support was all before the sale, however, we have a ton of IBM products and they provide the same high level of support for all of them. I didn't see this being any different. I give IBM support two thumbs up!
Read full review Alternatives Considered
We initially wanted to go with
, mainly for the name recognition. However, the pricing and support structure led us to seek alternatives, which pointed us to IBM.
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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MS SQL Server was ruled out given we didn't feel we could collapse environments. We thought of MS-SQL as more of a one for one replacement for Sybase ASE, i.e., server for server.
was evaluated and given a big thumbs up but was rejected because the SQL would have to be rewritten at the time (now they have an accelerator so you don't have to). Also, there was a very low adoption rate within the enterprise. IBM DB2 Big SQL was not selected even though technically it achieved high scores, because we could not find readily available talent and low adoption rate within the enterprise (basically no adoption at the time). We ended up selecting Exadata because of the high adoption rate within the enterprise even though technically HANA and Big SQL were superior in our evaluations.
Read full review Return on Investment 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 better data visibility solid reliability for mission critical data Read full review ScreenShots