Introduction
AGE acts as a link between two different worlds contained within a same database system. This blog examines the intriguing qualities of AGE and how it can transform the way we manage and get meaning from intricate data interactions. With AGE, you can combine the comfort of relational databases with the strength of graph databases to provide a unified and flexible solution for your data management needs.
AGE was created to give PostgreSQL, one of the most popular relational database management systems (RDBMS), access to graph databases' features. Lets see how we can use full power of AGE and Postgres to make a database which can handle both relational tables and graphs at the same time.
Unified Data Management
Through the usage of openCypher, a widely used graph query language, and ANSI SQL for structured data, users of AGE are able to quickly manage both relational and graph data models within a single database. These two technologies are seamlessly merged into a single database.
The Strength of PostgreSQL
AGE is based on the robust PostgreSQL architecture and benefits from its power and feature set. This includes support for multi-version concurrency control (MVCC), stored procedures, triggers, restrictions, and more. ACID (Atomicity, Consistency, Isolation, Durability) transactions are also included. To guarantee data confidentiality and integrity, AGE makes use of PostgreSQL's well-established dependability.
Effortless Integration
Making the switch to AGE is simple, especially for users who are accustomed to relational databases. No major reconfiguration or difficult data migrations are required. A hassle-free deployment of graph database capabilities is made possible by AGE, which effortlessly incorporates graph data analytics into your current PostgreSQL system.
Conclusion
Inshort not only can you use AGE for converting postgres into a graph database you can also use the full funcionality of postgreSQL without compromising any database or relations.
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