There are a huge number of AWS customers who use and depend on Amazon Dynamo DB for persistent performance for their serverless applications. Amazon Dynamo DB has a provisioned capacity model. Customers must set the amount of write and read operations that are required for their application. The introduction of auto-scaling helps to automate capacity management for tables and indexes on Amazon Dynamo DB. When using auto-scaling customers can state upper and lower bands for read and write capacity. After bands have been set by customer Dynamo DB will work with another Amazon service called CloudWatch to monitor and modify capacity when appropriate.
While Amazon Web Services typically offers a pay-as-you-go approach for its products, the company’s Relational Database Service (RDS) has been an outlier. Unlike Elastic Compute Cloud (EC2) instances, which can be paused and relaunched as needed, the ability to directly stop and start RDS instances has never been available… until now.
Functionality of DMS has been updated to support a leading no SQL database MongoDB
Amazon Web Services announced on the 10th of April that their Database Migration Service (DMS) functionality has been updated to support one of the leading Dev NoSQL databases –MongoDB. This new addition to the DMS allows for data to be streamed from a MongoDB along with any of the other supported databases on AWS.
In our previous blog post, we discussed ‘Which relational database engines does RDS support?’. We talked about the whole idea of Amazon RDS, is to allow you to move your relational databases to the cloud. In the second part of our blog discussing Amazon RDS, we are going to look at 6 amazing reasons to use Amazon RDS with your database engine.
Amazon’s Relational Database Service (RDS) is a tool provided by AWS that handles provisioning, patching, backup, recovery, failure detection and repair of your relational database. This leaves you with more time to concentrate on your data. The whole idea of RDS is to move your relational database to the cloud. It is easy to set up and operate and is also highly scalable, cost-efficient and saves time.
Both AWS services, Amazon Redshift and Amazon Relational Database Services (RDS) can be used together very effectively, in our latest blog, we are looking to find out the functions and features of both database services will allow the customer to identify the differences and which best meets their requirements.
Amazon Aurora is a relational database engine. It is designed to deliver the speed and reliability of high-end commercial databases in a simple and cost-effective manner. Amazon claims that it delivers up to five times the throughput of standard MySQL running on the same hardware. If you’re already using MySQL software for your database like a huge majority of people, Aurora is compatible with MySQL 5.6. This means that your existing MySQL applications and tools can still run on Aurora with no modification required.
Thousands of customers use Amazon DynamoDB to build popular applications for Gaming, Mobile, Ad-tech, Internet-of-Things and Modern Web applications. Developers all over the world are using Amazon DynamoDB to build applications that take advantage of its ability to provide consistent low-latency performance. Developers enjoy the flexibility provided by DynamoDB’s schema-less model, along with the ability to scale capacity up and down as needed. But we want to ask the question, does DynamoDB have a dependency on Amazon S3?