We checked a few solutions and tried solutions from Azure. There were pros and cons but this solution was more acceptable.

We used Oracle Exadata before using Apache Hadoop. It was one or two years ago when we started using the Apache Hadoop platform. We're still thinking about using both platforms in parallel or choosing one of the two. We're still looking into the benefits of each platform, but currently, we're using both Oracle Exadata and Apache Hadoop.

For some customers, we use Oracle Autonomous Database. Now, I cannot compare Apache Hadoop with Oracle Autonomous Data Warehouse when it comes to value for money. They're not directly comparable.

We selected Apache Hadoop because it is not dependent on third-party vendors. Previously, our main business unit was related to big vendors like IBM, Oracle, and EMC, etc. We wanted to have a competitive advantage in technology, so we selected the Apache project and used Apache open source.

I have since changed careers, I no longer use any automation tools, nor does my job need me to compare the capabilities of other tools.

I am working with Risk Analytic tools. I work with data these days, therefore I use technologies like Hive, Shiny R, and other data-intensive programs.

Shiny is a plugin that you can have on R. As a result of changing my profiles, I am now working in a position that is more data-centric and less focused on process automation.

We currently have proprietary tools, a proprietary cloud software, therefore I don't really need to employ any external cloud vendors. Aside from that, I only use the third-party technologies I've already indicated, primarily Hadoop and R.

This is one of the prime, one of the cornerstone software that we use. I have never been in a position to compare the like-for-like comparison with another software.

Some of our clients are using Teradata, and some of them are using Hadoop.

No. Two years ago this was a new team and hence there were no legacy systems to speak of.

There are the older relational database technologies: Netezza, SQL Server, MySQL, Oracle, Teradata. All have some advantages and some disadvantages. Most notably, they are all significantly more expensive in terms of the capital expense, rather than the operational expense. They are "walled-garden," so to speak, that are curated and have a distinct set of tools that work with them, and not the bleeding-edge ingenuity that comes with an open-source platform.

Data warehousing is 30 years old, at least. Big data is, in its current form, has only been around for four or five years old.

We started off using Apache Hadoop for our initial Big Data initiative and have stuck with it since.

We used the more traditional database solutions such as SAP IQ  and Data Marks, but now it's changing more towards Data Science and Big Data.

We are a smaller infrastructure, so that's how we are set up.

We have only ever used Apache Hadoop, or a version of it. When we looked for the commercial tier, there was Cloudera and Hortonworks. We started with the Hortonworks due to the fact that at that time we felt it was cost-effective. However, Cloudera bought Hadoop and Hortonworks and now it's all basically the same solution.  

We previously used Netezza. We switched because our business required a highly scalable appliance like Hadoop.

We had a very old version of Hadoop which was already installed by another company and we upgraded it. We didn't really switch we just upgraded what was here.

I've also worked with MySQL and Postgres. Hadoop is more for analytical processing. While the others claim to have a distributor, Hadoop is far better in that regard. It's excellent compared to other options.

We didn't previously use a different solution.

We didn’t have a previous solution. It was a move from RDBMS to big data.