NoSQL Benchmarks NoSQL use cases NoSQL Videos NoSQL Hybrid Solutions NoSQL Presentations Big Data Hadoop MapReduce Pig Hive Flume Oozie Sqoop HDFS ZooKeeper Cascading Cascalog BigTable Cassandra HBase Hypertable Couchbase CouchDB MongoDB OrientDB RavenDB Jackrabbit Terrastore Amazon DynamoDB Redis Riak Project Voldemort Tokyo Cabinet Kyoto Cabinet memcached Amazon SimpleDB Datomic MemcacheDB M/DB GT.M Amazon Dynamo Dynomite Mnesia Yahoo! PNUTS/Sherpa Neo4j InfoGrid Sones GraphDB InfiniteGraph AllegroGraph MarkLogic Clustrix CouchDB Case Studies MongoDB Case Studies NoSQL at Adobe NoSQL at Facebook NoSQL at Twitter



Operations on Graph Databases

The InfoGrid blog has started to publish a series on basic operations with graph databases. While it looks like getting a taste of graph databases was a very good start, it wasn’t meant to introduce the details of working with a graph database, something that people may not be familiar with.

So, here are the first three articles on operations with a graph database:

  1. ☞ Nodes
  2. ☞ Edges and Traversals
  3. ☞ Typing (from free form nodes/edges to “strongly typed” nodes/edges)
  4. ☞ Properties
  5. ☞ Identifiers
  6. ☞ Traversals

    Traversals are the most common operations on a graph database. They are just as important for graph databases as joins are for relational databases.

  7. ☞ Sets (new)

    Sets are a core concept of most databases. […] Sets apply to Graph Databases just as well and are just as useful:

    The most frequently encountered set of nodes in a Graph Database is the result of a traversal.

I just hope the series will keep going!