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I'm considering a setup where I have entities stored both in a document db (e.g. CouchDB) and a graph db (e.g. Neo4j). The rationale is storing each entity information (data, blobs, values, complex internal structure) in the document db while storing the entity relations (parents, children, associated entities) in the graph db.
Has anyone done / seen / been bitten by a setup like this? What kind of issues should I expect? First thing that come to mindaka the 2-phase commit. But backups are problematic too here.
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asked Aug 30 '12 03:08
Graph databases are not as useful for operational use cases because they are not efficient at processing high volumes of transactions and they are not good at handling queries that span the entire database.
Complex queries typically run faster in graph databases than they do in relational databases. Relational databases require complex joins on data tables to perform complex queries, so the process is not as fast.
Neo4j is an OLTP graph database which excels at querying data relationships, which is a weakness of other NoSQL and SQL solutions. We created the Neo4j Doc Manager for Mongo Connector to allow MongoDB developers to store JSON data in Mongo while querying the relationships between the data using Neo4j.
Graph databases have advantages for use cases such as social networking, recommendation engines, and fraud detection, when you need to create relationships between data and quickly query these relationships. The following graph shows an example of a social network graph.
You may check out the book "Seven DBs in Seven Weeks". 8th chapter talks about building up a polyglot structure via CouchDB, Neo4j and Redis.
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