Here are some of the better known open source data stores/models labeled as "NoSQL":
CouchDB - Document Store
- Maps keys to data
- It provides a RESTful JSON API and is written in Erlang
- You can upload functions to index data and then you can call those functions
- Has a very simple REST interface
- Provides an innovative replication strategy - nodes can reconnect, sync, and reconcile differences after being disconnected for long periods of time
- Enables new distributed types of applications and data
MongoDB - Document Store
- Free-form key-value-like data store with good performance
- Powerful, expansive query model
- Usability rivals that of Redis
- Good for complex data storage needs.
- Production-quality sharding capabilities
Neo4j - GraphDB
- Has a restricted, single-threaded model for graph traversal
- Has optional layers to expose Neo4j as an RDF store
- Can handle graphs of several billion nodes, relationships, or properties on a single machine
- Released under a dual license - free for non-commercial use
Apache Hbase - Wide Column Store/Column Families
- Built on top of Hadoop, which has functionality similar to Google's GFS and MapReduce systems
- Hadoop's HDFS provides a mechanism that reliably stores and organizes large amounts of data
- Random access performance is on par with MySQL
- Has a high performance Thrift gateway
- Cascading source and sink modules
Redis - Key Value/Tuple Store
- Provides a rich API and does more operations in memory, using disk only periodically.
- It's extremely fast
- Lets you append a value to the end of a list of items that's already been stored on a key.
- Has atomic operations, making it a best-of-breed tally server.
Memcached - Key Value/Tuple Store
- High-performance, distributed memory object caching
- Free and open source
- Generic and agnostic to the objects/strings it caches
- It's all in-memory data
- Simple yet elegant design enables easy development and deployment
- Language neutral caching scheme.
- Most of the large properties on the web are using it now, except for Microsoft
Project Voldemort - Eventually Consistent Key Value Store
- Used by LinkedIn
- Handles server failure transparently
- Pluggable serialization supports rich keys and values including lists and tuples with named fields
- Supports common serialization frameworks including Protocol Buffers, Thrift, and Java Serialization
- Data items are versioned
- Supports pluggable data placement strategies
- Memory caching and the storage system are combined
Tokyo Cabinet and Tokyo Tyrant - Key Value/Tuple Store
- Supports hashtable mode, b-tree mode, and table mode
- It's fast and straightforward
- Good for small to medium-sized amounts of data that require rapid updating and can be easily modeled in terms of keys and values
Cassandra - Wide Column Store/Column Families
- First developed by Facebook
- SuperColumns can turn a simple key-value architecture into an architecture that handles sorted lists, based on an index specified by the user.
- Can scale from one node to several thousand nodes clustered in different data centers.
- Can be tuned for more consistency or availability
- Smooth node replacement if one goes down
Some other well known NoSQL-style data stores that are closed source include Google BigTable and Amazon SimpleDB. GigaSpaces is a popular space-based Grid solution that has NoSQL qualities.
Check out this informative post on NoSQL patterns.