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Moiz Ibrar
Moiz Ibrar

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Scalable Data Analysis with Postgres and Apache AGE: A Case Study part 2

*Benefits *
Data Solutions Inc. gained a lot of benefits by using Apache AGE. One of the most important was the special search language called GQL, which made it easier and more natural for them to find and analyze their data.

By adding Apache AGE to their Postgres database, they could handle more data and search it faster. This meant they could keep up with the growing amount of information from their customers and not be overwhelmed by it.

The new system also gave them better insights into what their customers were doing, which allowed them to make faster and better decisions. By having a more scalable and powerful system, they could get the information they needed more quickly and easily.

Summary
Data Solutions Inc. was able to handle their growing amount of data by adding Apache AGE to their existing Postgres database. This combination allowed them to store and analyze large amounts of complex data more efficiently without having to change their entire system.

The new system was powerful and flexible, which meant they could manage their data more effectively and easily. By doing this, they were able to keep up with the growing amount of information from their customers and make better decisions faster.
Apache-Age:-https://age.apache.org/
GitHub:-https://github.com/apache/age

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