Amazon RDS

There were plenty of custom web application running on our customer environment in local DB setup. It required lot of admin efforts and it caused development inefficiency. I researched and proposed the AWS RDS as out customer was having AWS platform already. With AWS RDS we cut down the efforts in managing the softwares and admin tasks. We are able to scale up as per demand for some high usage applications without any heckle.

We use Amazon Aurora as one of the databases used for hosting a product in our Edtech SaaS Platform GIDE.AI.

As a Relational Database Service we have used AWS RDS because as a Banking and Fintech organisation we are dealing with millions of customer and as AWS provides this Managed service which is fully fledged with lots of feature like High Availability, Fault Tolerance, Security measures, In Depth Monitoring, Resilency, Query Suggestions and Very High Performance. Moreover this all set of features are available as one click solutions so we don't have a external headache to manage the Database we just have to focus on our Application.

We started using RDS as an alternative to our BE system since, at the beginning, the team did not have experience or knowledge about BE frameworks, but it was necessary to maintain a relationship between the data of the projects being executed and the RDS services of Amazon were of great help, since it is an out of the box solution. As well as it also served as a starting point to understand how our BE system should be structured later.

Our company needed a reliable and fast solution for storing our customer data and Amazon Relational Database Service was a good choice because of all the set of features it offers. On top of the relational storage, our company could comply with market standards by easily having replication, backup, patching and user management easily implemented natively in the solution. What is also great about Amazon Relational Database Service is that you can manage everything using terraform, making it easy to reproduce the configurations in multiple environments.

Amazon Relational Database Service (RDS) is used in our company at quite a large scale. We have migrated all of our server infrastructure to the Amazon Web Services (AWS) cloud, so making use of the Relational Database Service was a no-brainer for us.
Most of our systems are connected to an RDS instance.

In healthcare, managing patient records and sensitive data securely is crucial. RDS offers encrypted storage, ensuring data security and compliance with regulations like HIPAA (Health Insurance Portability and Accountability Act). This encryption extends to data in transit and at rest. With RDS, you can set up multi-AZ (Availability Zone) deployments for high availability. This is vital in healthcare, where database downtime can directly impact patient care. In case of disasters, RDS facilitates quick recovery, minimizing data loss.

We use RDS to manage all of our SQL databases for multiple billing and payment applications. This includes Aurora and PostgreSQL databases with millions of records and several terabytes of data. These databases are accessed in real time by web applications that handle the requests from thousands of users. RDS handles backups, security, and compliance by default.

I used Amazon Relational Database Service for Databricks Technical Field Telemetry(TFT) Project, which is an internal project for field engineering teams where they manage customer engagement, interactions, feedbacks. This majorly helped to improve our product by managing each team, each individual performances, thus they can set targets for improvement plans. It also displays a hit score which is the benchmark for internal teams. We used Amazon Relational Database Service serverless to deploy the backend database, which is lightening fast, reliable DBMS.

RDS simplifies database management tasks like provisioning, patching, backup, recovery etc. This reduces the administrative burden and allows teams to focus on application development rather than database maintenance. Since this is a managed service it provides in built high availability and scalability. Also we can secure our data by encrypting them at both transit and rest. One more useful use case is, we can selectively encrypt sensitive data to give extra protection

Storing relational auditing data for our digital ecosystem which includes desktop website, mobile website and mobile apps to get meaningful insights so as to take next steps.

In my organization we use Amazon Relational Database Service (RDS) for storing relational data which is used by our Internal teams for their workloads. In our current use case Amazon RDS addressed the problems of managing the Database, offer scalability and High availability on demand reducing the operational burden on the team.

We utilize Amazon Relational Database Service to host MySQL RDBS to store the data related to custom apps for our dev environment. It's super easy & fast to set up the database instances in a few clicks from the AWS management console. A lot of times, the developers in our team aren't that expert when it comes to managing the database administration, & hence for this very reason, Amazon Relational Database Service is our preferred DB service as it simplifies time-consuming admin tasks.

We have Amazon Relational Database Service (RDS) and is used for application level data access for custom applications

RDS performs frequent backups of your database, and you may configure retention rules to control how long backups are kept. RDS makes it simple to extend our database instance vertically by switching instance types or horizontally by adding read replicas. AWS takes care of the underlying infrastructure, including hardware provisioning, database setup, patching, and backups of our business.

We at Publicis Sapient has been delivering software solutions to many of our clients regularly. There is often the need to persistent data storage and we recommend to use Amazon RDS because it is easy to set up, the dev team don't have to dig deep in understanding about how to connect the Amazon RDS to the backend or how to invoke a request. The Amazon RDS has low learning curve which means the new dev team can work on it from day 1 without good deeper in terms of learning.

We use RDS as part of the infrastructure as a service that supports our application. In the beginning, we struggled a bit with fine-tuning and monitoring but once we incorporated the tools everything worked very well. I consider that the scalability and backup tools are adequate for our requirements.
While availability and provisioning speed are similar to other IaaS, they are still important.

I utilize Amazon RDS as the backbone for content management and stored user information for our corporate web presence. I was looking for a scalable relational database that would be an easy transition with my background in MySQL. I didn't want to spend a lot of time setting up and managing replication and backup, and I didn't want daily maintenance tasks. RDS fit the bill nicely, and coupled with my EC2-based web hosting, provides a easy-to-implement security.

RDS is pivotal to our data strategy, powering hundreds of databases within our infrastructure. Its reliability and scalability ensure optimal performance and data integrity. Rigorous security measures, including backups and monitoring, maintain database stability. RDS flexibility accommodates evolving business needs while optimizing performance and cost-efficiency.

We are using RDS in storing all our products and their information.
We have hundreds of brass products and we have maintained all our product database with RDS.
It is quick and easy also we have assigned to roles to avoid access to unauthorized users.
We have different databases of products depending upon our audience and purpose.

We use RDS as a database service provider for multiple eCommerce and small business websites to deliver configuration and content data to several mainstream service softwares. We use this as a rate-based, scalable alternative to cPaneled phpMyAdmin setups. More control means throughput and service level can be increased instead of being subject to server limitations.

Adding read replicas or growing our database laterally (by adding instances) or vertically (by increasing instance size) is simple with RDS. This adaptability guarantees that our database can manage rising workloads. RDS offers daily automated backups and lets our specify retention times. Providing choices for data recovery, we can restore our database to any point throughout the retention term.

A certain business school have several data bases that are permanently updated with data coming from various sources. The challenge is that these data have several formats and templates, making it compliex to manage in an efficient and economic way. The need for a tool such as Amazon Relational Database Service (RDS) was imperative to improve management.

During one of our recent e-commerce projects, we encountered a significant database infrastructure challenge. The rapid growth in product listings and customer data led to frustratingly slow response times and concerns about data integrity. To address these issues, we made a strategic decision to migrate our database to Amazon RDS, which proved to be highly effective in bringing about remarkable improvements. Amazon RDS became the cornerstone of our database management strategy, offering enhanced reliability and high availability through automated backups and multi-AZ deployments. These RDS features ensured that our database remained up-to-date, secure, and consistently accessible for seamless operations. In particular, Amazon RDS played a pivotal role in significantly boosting website performance, elevating data reliability, and establishing a cost-efficient approach to database management. These contributions were instrumental in the overall success of our project, highlighting the transformative impact of Amazon RDS on our e-commerce venture.

Amazon Relational Database Service (RDS) is simple to setup and makes scaling database in cloud a very easy task during high load scenarios. It supports backup and recovery. Amazon Relational Database Service (RDS) offers identity management that ensures people with assigned roles can only access the data. Amazon Relational Database Service (RDS) ensures availability of the workloads at all times and hence suited for production. It offers third party integrations also.