Seems like the industry is getting hit with a new analytics solution for "big data" every couple of weeks. With every database vendor and analytics provider jumping into this space, we wanted to offer a checklist of questions for you to ask – so you can start differentiating between the options in the marketplace.

Start with the questions here, and then be sure to add some of your own as well that speak specifically to the type of business problem you’re trying to solve with big data.

1. Do you provide multiple deployment options for high-performance analytics?
2. Can you work with multiple database providers to find the right fit for my IT environment?
3. Do I need to learn a new programming technique to use your product, or can I work with the one I already know?
4. Does your solution require DBA performance tuning?
5. How do you define advanced analytics? Does your big data solution address the needs of classification, clustering, forecasting, association and optimization?
6. Can I integrate analytic insights from your high-performance product in to my existing processes or into intelligent actions?
7. Can your solution scale beyond a few terabytes or is it limited to the hardware limitations of a single server?
8. Does your in-memory architecture run on commodity blades or specialized hardware platforms?
9. Does your in-memory solution hold or persist data in-memory for multiple users and multiple passes at the data?
10. Can you provide visualization results customized for exploratory analysis of big data sources?
11. Do your visualizations include descriptions of the data and options for filtering different hierarchies of the data?
12. Can you integrate directly with Hadoop without building layers on top of Hadoop or constructing pipelines with Hive, Pig or other solutions?

Of course, this list isn’t comprehensive. We could add questions all day about data quality, complex visualizations and predictive analytics on big data. If you have some that you’ve found useful or think are essential to the vendor selection process, contribute your questions to the comment area or send them to us on Twitter.

Or, you might find the answers to your tough "big data" questions in this special 32-page report on high-performance analytics.