Roberto Zicari from ODBMS.ORG asked 10 questions to Robert Greene, CTO and V.P. Open Source Operations at Versant.

  1. Traditionally, the obvious platform for most database applications has been a relational DBMS. Why do we need new Data Stores?
  2. There has been recently a proliferation of “new data stores”, such as “document stores”, and “nosql databases”: What are the differences between them?
  3. How new data stores compare with respect to relational databases?
  4. Systems such as CouchDB, MongoDB, SimpleDB, Voldemort, Scalaris, etc. provide less functionality than OODBs and are little more than a distributed “object” cache over multiple machines. How do these new data stores compare with object-oriented databases?
  5. With the emergence of cloud computing, new data management systems have surfaced. What is in your opinion of the direction in which cloud computing data management is evolving? What are the main challenges of cloud computing data management?
  6. What are cloud stores omitting that enable them to scale so well?
  7. Will cloud store projects end up with support for declarative queries and declarative secondary keys?
  8. In his post, titled “The “NoSQL” Discussion has Nothing to Do With SQL”, Prof. Stonebraker argues that “blinding performance depends on removing overhead. Such overhead has nothing to do with SQL, but instead revolves around traditional implementations of ACID transactions, multi-threading, and disk management. To go wildly faster, one must remove all four sources of overhead, discussed above. This is possible in either a SQL context or some other context.” What is your opinion on this?
  9. Some progress has also been made on RDBMS scalability. For example, Oracle RAC and MySQL Cluster provide some partitioning of load over multiple nodes. More recently, there are new scalable variations of MySQL underway with ScaleDB and Drizzle, and VoltDB is expected to provide scalability on top of a more performant inmemory RDBMS with minimal overhead. Typically you cannot scale well if your SQL operations span many nodes. And you cannot scale well if your transactions span many nodes. Will RDBMSs provide scalability to 100 nodes or more? And if yes, how?
  10. There is also xml DBs, which go beyond relational. Hybridization with relational turned out to be very useful. For example, DB2 has a huge investment in XML, and it is extensively published, and it has also succeeded commercially. Monet DB did substantial work in that area early on as well. How do they relate with “new data stores”?

To see the answers head to ODBMS.ORG