Adjustable, versioned graph database

Question

I\'m currently working on a project where I use natural language processing to extract emotions from text to correlate them with contextual information.

Definition o

Answer 1

There is an obvious 1:1 correspondence between your states at a given time and a relational database with a given schema. So there is an obvious 1:1 correspondence between your set of states over time and a changing-schema database, ie a variable whose value is a database plus metadata, manipulated by both DDL and DML update commands. So there is no evidence that you shouldn't just use a relational DBMS.

Relational DBMSs allow generic querying with automated implementation at a certain computational complexity with certain opportunities for optimization. Any application can have specialized queries that make a specialized data structure and operators a better choice. But you must design your application and know about such special aspects to justify this. As it is, with the obvious correspondences between your states and relational states, this has not been justified.

EAV is frequently used instead of DDL and a changing schema. But under EAV the DBMS does not know the real tables you are concerned with, which have columns that are EAV attributes, and which are explicit in the DDL/DML changing schema approach. So EAV foregoes simplicity, clarity, optimization and most of all integrity and ACID. It can only be justified (compared to DDL/DML, assuming a relational representation is otherwise appropriate) by demonstrating that DDL with schema updates (adding, deleting and changing columns and tables) is worse (per the above) than EAV in your particular application.

Just because you can draw a picture of your application state at some time using a graph does not mean that you need a graph database. What matters is what specialized queries/expressions you will be evaluating. You should understand what these are in terms of your problem domain, which is probably most easily expressible per some specialized data structure and operators and relationally. Then you can compare the expressive and computational demands to a specialized data structure, a relational representation, and the models of particular graph databases. Be sure to google stackoverflow.

According to Wikipedia "Neo4j is the most popular graph database in use today".