EVP Technology at a consultancy with 51-200 employees
Real User
Top 5
2023-05-03T07:07:00Z
May 3, 2023
We had challenges in loading huge volumes of data quickly, with reports growing beyond a certain number of millions of rows. Despite indexing and applying filters, we experienced significant latency loading the related reports. That's why we looked into using Aurora. We monitored it for about six months and tweaked the database-related parameters, but we still didn't see much improvement. So we reverted to RDS.
Owner at a computer software company with 1-10 employees
Real User
Top 20
2023-02-17T13:34:26Z
Feb 17, 2023
I am using Amazon Aurora as a relational database. Our applications for our business users are usually relatively internal application types which are mostly small, which makes data storage and retrieval quick and easy, especially when developing business applications where time is of the essence. Therefore, it is preferable to have a technology that allows developers to work quickly and seamlessly, without any complicated setup or extra steps. When we use NoSQL databases the data comes at a high speed.
Amazon Aurora is a relation database built on top of a Postgre or MySQL engine. These days, we are mostly developing small microservices, and we consider Aurora if we want to have a scalable database. It can have a higher number of read replicas. In those instances, we recommend Aurora. With one or two projects, we have used Aurora. The solution is deployed on their managed service on the cloud.
What is a relational database? A database is an organized collection of structured data that is electronically stored in a computer system.
A relational database is an intuitive database that stores and supplies access to various related data points. A relational database is based on the relational model where data is stored in tables in an intuitive and straightforward way, similar to an Excel spreadsheet. In this management system, tables are used to store complex data, which can be...
I use Aurora for data storage.
I use Amazon Aurora for the high availability of MySQL cluster solutions.
We had challenges in loading huge volumes of data quickly, with reports growing beyond a certain number of millions of rows. Despite indexing and applying filters, we experienced significant latency loading the related reports. That's why we looked into using Aurora. We monitored it for about six months and tweaked the database-related parameters, but we still didn't see much improvement. So we reverted to RDS.
The solution is auto-scalable and serverless. It runs on the background and automatically scales up incase of heavy loads.
I am using Amazon Aurora as a relational database. Our applications for our business users are usually relatively internal application types which are mostly small, which makes data storage and retrieval quick and easy, especially when developing business applications where time is of the essence. Therefore, it is preferable to have a technology that allows developers to work quickly and seamlessly, without any complicated setup or extra steps. When we use NoSQL databases the data comes at a high speed.
Our deployment was only used within the organization. We didn't make it available publically.
Amazon Aurora is a relation database built on top of a Postgre or MySQL engine. These days, we are mostly developing small microservices, and we consider Aurora if we want to have a scalable database. It can have a higher number of read replicas. In those instances, we recommend Aurora. With one or two projects, we have used Aurora. The solution is deployed on their managed service on the cloud.