Storage of Data
Better for complex read queries. Fast querying of
data. Storage of very large quantities of data. Better
analytic performance. Improved data compression.
Powerful data model. Locally connected data. Indexed data. Easy to
query. Handling complex relational information.
Cons Stored data have no schema. Poor for
complex data. All joins must be done in code.
No foreign key constraints. No triggers.
Query model limited to keys and indexes.
No standard query syntax. Map Reduce for larger
queries. Poor for interconnected data.
Very low-level API. Undefined data usage pattern.
Increased disk seek time. Increased cost of inserts.
Poor for interconnected data.
Travers entire graph to give correct results.
Sharding.
Suitable for Storing session’s, information, user
profiles, preferences, shopping cart data.
Content management systems, blogging
platforms, web analytics, real-time analytics,
e-commerce applications.
Content management systems, blogging platforms,
maintaining counters, expiring usage, heavy write
volume such as log aggregation.
Space problem and connected data, such as social networks, spatial
data, routing information for goods and money,
recommendation engines. Examples Riak
Redis MemcacheDB
Dynamo Voldemort
MongoDB CouchDB ArangoDB MarkLogic RzthinkDB
BigTable Habse
Casandra Accumulo Hypertable
Neo4j OrientDB Allegro Virtuoso
