April 14, 2013

Introduction to Deep Information Sciences and DeepDB

I talked Friday with Deep Information Sciences, makers of DeepDB. Much like TokuDB — albeit with different technical strategies — DeepDB is a single-server DBMS in the form of a MySQL engine, whose technology is concentrated around writing indexes quickly. That said:

*For reasons that do not seem closely related to product reality, DeepDB is marketed as if it supports “unstructured” data today.

Other NewSQL DBMS seem “designed for big data and the cloud” to at least the same extent DeepDB is. However, if we’re interpreting “big data” to include multi-structured data support — well, only half or so of the NewSQL products and companies I know of share Deep’s interest in branching out. In particular:

Edit: MySQL has some sort of an optional NoSQL interface, and hence so presumably do MySQL-compatible TokuDB, GenieDB, Clustrix, and MemSQL.

Also, some of those products do not today have the transparent scale-out that Deep plans to offer in the future.

Among the 10 people listed as part of Deep Information Sciences’ team, I noticed 2 who arguably had DBMS industry experience, in that they worked at virtualization vendor Virtual Iron, and stayed on for a while after Virtual Iron was bought by Oracle. One of them, Chief Scientist & Architect Tom Hazel, also was at Akiban for a few months, where he did actually work on a DBMS. Other Deep Information Sciences notes include:

Although our call was blessedly technical, we didn’t have a chance to go through the DeepDB architecture in great detail. That said, DeepDB seems to store data in all of 3 ways:

Notes on that include:

And finally: DeepDB in its current form is a “drop-in” InnoDB replacement, but not necessarily bug-compatible.


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