Need a graph database? Look no farther than Neo4j

Robert Scoble and Emil Eifrem discuss Neo4j, graph databases and BBQ restaurants.

Couple of notes taken from the interview:

• There are a lot of interesting integrations of social and geographic graphs that have yet to be explored.
• Neo4j more general purpose and supports infinite depth. This is contrast to a specialized solution like Twitter's FlockDB which is geared towards Twitter's unique needs.
• Graph databases excel whenever the value is in the connections.
• How scalable is Neo4j?
  
  • It's really challenging to provide horizontally when dealing with a graph database.
  • Neo4j scales to 12 billion nodes and relationships.
  • Currently relies on replication of the entire graph across machines.
• In Neo4j 2.0 they are implementing transparent partitioning. Transparent partitioning essentially attempts to place isolated clusters of a graph, on their own machine. It's a difficult problem to solve simply because two isolated clusters can become connected with just one link.
• Neo4j uses AGPL license. Essentially if your service is open source, Neo4j is open source. If your service is going to be closed source you need to purchase a commercial license.

Cloudera's CEO talks us through big data trends

Really good interview by Robert Scoble with Mike Olsen the CEO of Cloudera. It touches on a number of topics including Hadoop, Big Data and NoSQL. There are some mentions of NoSQL technologies such as MongoDB, CouchDB and Cassandra. Regardless, Mike Olsen is a very engaging guy and is very interesting to listen to. Despite being focused on Hadoop and Cloudera it's worth checking it out.