Data migration is one of the necessary evils involved with keeping a database aligned with the evolving needs of the business and applications using it. With the increasing demand for enterprises of all sizes to iterate more quickly and drive change from within the data migration conversation becomes much more frequent. Data migration procedures are something that can take a very long
Data migration is not just an enterprise issue. Startups are changing at even more rapid rate while they iterate on their product(s) and business model(s) trying to figure out exactly what they need to be. Being able to perform rapid, low risk data migrations with minimal impact to existing applications using the database is one great benefit of Neo4j with it’s flexible schema-free data model.
Neo4j Graph Database Data Migration
As a native graph database Neo4j provides several advantages when it comes to managing data migrations:- Neo4j treats relationships as primary entities within the database which means you can add a new relationship to connect certain nodes in a new way without needing to migrate a table schema enforcing a new foreign key along with inserting all the corresponding references into each row in the table or building a JOIN-table.
- Neo4j uses labels to index common nodes. A label is like a tag and node can have any number labels. Labels are useful in a data migration because while they associate nodes together under a certain type they don’t bring with them, by default, a schema definition containing properties, data types and the like that must be adhered to by any node given that label. This means you can temporarily group a set of
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