IBM Db2 Warehouse on Cloud Reviews

Our primary use case is data storage and analytics.

The organization has decided to purchase a full stack solution from IBM due to positive responses, which helped them upgrade from the previous version.

IBM has taken a new approach to database technology.

One of the most amazing features of dashDB is how it uses compression to get results in lighting speed. dashDB uses advanced processing which doesn't require the entire dataset to fit in memory.

Prefetching of data: Has the ability to anticipate and "prefetch" data just before it's needed and to automatically adapt to keep necessary data in, or close, to the CPU.

No Decompression Required: dashDB preserves the order of data and performs a broad range of operations including joins and predicate evaluations on compressed data, without the need for decompression, drastically speeding the processing of data.

Data Skipping: dashDB's BLU acceleration automatically determines which data would not qualify for analysis within a particular query, enabling large chunks of data to be skipped.

I believe that many organizations need to look at how they are servicing their customers. dashDB doesn't necessarily replace your existing infrastructure. However, as an add-on, you can now expand your overall operations and performance goals.

This is part of our Data Warehouse solution and it is set up as a two-node cluster.

The performance is okay as long as the volume of queries is not too high.

The cloud DBMS solution is most valuable to us.

Since my company is an IBM partner, it has enabled us to offer cloud data warehouse solutions on a 100% IBM stack.

I like that the dashDB solution is built on DB2 technology. This means that you can use all the features of a DB2 database, but outsource all the hardware and software maintenance. Cloud solutions/services are the big thing for the future. IBM has provided users with the ability to store data in the cloud with the option to use the database as a MPP server.

The organization (a customer of ours) has used it to create a sort of data hub to use as a foundation for other business applications, such as self-service BI and online web services.

IBM dashDB’s availability on the cloud and integration with IBM Bluemix gives universal access to our teams that are spread over different geolocations. It’s a high-performance columnar database and stores data at 10x compression in comparison to traditional RDMBS systems.

For us, we have large volumes of data to store and analyze, i.e., around 2-10 GB daily data in flat file formats and with high compression ratio; thus we save a lot of space on the cloud.

IBM dashDB comes with some unique features like integrated RStudio, a full scale database management studio (IBM Data Studio) and web-based management console that makes using this product easy.

It also offers SMP as well as MPP instances where MPP is a 3-or-more node cluster for big data storage and analysis.

Our analytics teams really like the integrated RStudio feature with which they can instantly connect to structured data and do their analysis. Traditionally, our analytics team would ask for data in flat files. They had to write the codes in order to clean and import the files and only then could they start the analysis part.

Now, the ETL team takes care of importing the data to dashDB and our data science team can focus on building the models. Once the model is developed, our modeling team can save the results in dashDB, which can be instantly used by our presentation apps. This is much easier and faster to work with instead of using the CSV files in all steps of data sharing.

The warehouse DB/dashDB implementation scales a lot better that IBM BLU does. It will also be MPP, so performance should improve.

Ease of migration from Netezza DB. IBM ported over all Netezza's functionality and made the warehouse DB/dashDB the best of breed of the two.