Where Datameer is positioned
I’ve chatted with Datameer a couple of times recently, mainly with CEO Stefan Groschupf, most recently after XLDB last Tuesday. Nothing I learned greatly contradicts what I wrote about Datameer 1 1/2 years ago. In a nutshell, Datameer is designed to let you do simple stuff on large amounts of data, where “large amounts of data” typically means data in Hadoop, and “simple stuff” includes basic versions of a spreadsheet, of BI, and of EtL (Extract/Transform/Load, without much in the way of T).
Stefan reports that these capabilities are appealing to a significant fraction of enterprise or other commercial Hadoop users, especially the EtL and the BI. I don’t doubt him.
| Categories: Business intelligence, Datameer, EAI, EII, ETL, ELT, ETLT, Hadoop | Leave a Comment |
Introduction to Datameer
Elder care issues have flared up with a vengeance, so I’m not going to be blogging much for a while, and surely not at any length. That said, my first post about Datameer was never going to be very long, so lets get right to it:
- Datameer offers a business intelligence and analytics stack that runs on any distribution of Hadoop.
- Datameer is still building a lot of features that it talks about, for target release in (I think) the fall.
- Datameer’s pride and joy is its user interface. Very laudably for a software start-up, Datameer claims to have spent considerable time with professional user interface designers.
- Datameer’s core user interface metaphor is formula definition via a spreadsheet.
- Datameer includes 124 functions one can use in these formulae, ranging from math stuff to text tokenization.
- Datameer does some straight BI, with 4 kinds of “visualization” headed for 20 kinds later. But if you want to do hard-core BI, use Datameer to dump data into an RDBMS and then use the BI tool of your choice. (Datameer’s messaging does tend to obscure or even contradict that point.)
- Rather, Datameer seems to be designed for the classic MapReduce use cases of ETL and heavy data crunching.
- Datameer’s messaging includes a bit about “Datameer is real-time, even though Hadoop is generally thought of as batch.” So far as I can tell, what that boils down to is …
- … Datameer will let you examine sample and/or partial query results before a full Hadoop run is over. Apparently, there are three different ways Datameer lets you do this:
- You can truly query against a sample of the data set.
- You can query against intermediate results, when only some stages of the Hadoop process have already been run.
- You can drill down into a “distributed index,” whatever the heck that means when Datameer says it.
- Datameer will let you import data from 15 or so different kinds of sources, SQL, NoSQL, and file system alike.