With organizations looking for more flexible backend solutions, NoSQL databases are gaining traction. The sophistication of big data and the proliferation of modern web applications have triggered the adoption of NoSQL databases to deliver scalable, distributed cloud performance.  

No SQL databases provides a method to store and retrieve data that involves a multitude of data structures such as graphs, key-values, wide columns, and documents. In order to manage huge volumes of structured, semi-structured, and unstructured data, NoSQL databases require no predefined schema and facilitate faster application development, application modifications, and less administrative overhead.  

NoSQL offers faster performance as a result of non-relational data structures. The ability to scale and take advantage of the cloud data centers gives NoSQL an edge over relational databases in the media, retail, IoT, finance, and healthcare industries.  

Amazon RDS 

Amazon Relational Database Service (RDS) is a managed SQL database service that automates all the time-consuming administration tasks such as provisioning, setup, patching, and backups.  

RDS is the best candidate to move on-premise database workloads to the cloud and helps automate the administrative activities associated with managing databases.  

Many organizations are adapting RDS because Amazon handles high availability, recovery, backups, and patching.  

  • With Multi-AZ deployment, Amazon RDS creates synchronous master pairs across various availability zones. If an unexpected outage happens, RDS will failover to a standby duplicate present in a different availability zone. This way, RDS guarantees data redundancy, failover support, and minimal latency during system backups.  
  • AWS RDS read replicas offer multiple read-only copies of your database instance within the same or a different AWS availability zone. With AWS RDS, you get multiple benefits including fault-tolerant availability, load balancing for high volumes of read traffic, and scalability for read-heavy workloads.  

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MongoDB Performance 

MongoDB is a widely implemented NoSQL database which is deployed on mainframes, on-premise, hybrid cloud, as well as a service on AWS. MongoDB is most suited for internet-scale applications because of its distributed scalability, data validation rules, and extensive monitoring capabilities.  

Key capabilities of MongoDB include allowing cloud architects to optimally configure resources and system administrators among many others: 

  • Distributed architecture that complies with automated sharing and allows for optimal location of data to support low-latency.  
  • High-availability clusters that support an uptime SLA of 99.99% across all CSPs.  
  • A minimum of 3 data nodes per replica set are deployed across the AWS availability zones for continuous application uptime.  
  • Document-oriented database stores data in a binary-encoded JSON format which increases speed and flexibility.  
  • Complex queries are solved natively to minimize latency. Additional analytics frameworks or tools aren’t necessary.  
  • Extensive monitoring dashboard and customized alerting provide metrics on database performance.  

DynamoDB Performance 

Amazon DynamoDB is a key-value and document database tailor-made for internet-scale mobile, web, gaming applications that require low-latency data access. More than 100,000 AWS customers leverage DynamoDB as it simplifies implementation and management. DynamoDB doesn’t need servers to manage and no software to install or maintain.  

The key performance capabilities of DynamoDB include:  

  • Tables automatically replicate data across AWS regions, allowing globally distributed applications to access data locally.  
  • Automatically scales tables to comply with capacity and performance.  
  • A monthly SLA uptime of 99.99% for each AWS region.  
  • Fully managed in-memory caching significantly reduces read time to microseconds.  
  • 100 TBs of backup doesn’t affect application performance.  
  • Application performance monitoring scales throughput and storage.  

DynamoDB vs MongoDB Performance Considerations 

MongoDB runs on multiple cloud platforms, scales horizontally across geographies, and offers sophisticated performance monitoring capabilities. The ability to run across various CSPs including Azure, AWS, and GCP makes MongoDB the perfect choice for businesses that develop and manage applications in multi-cloud environments.  

However, businesses that are planning or that have already invested in AWS and looking for a NoSQL database, DynamoDB is the logical choice. Businesses can enjoy several benefits including ease of deployment, automated management, and integration with other AWS services.  

Although businesses are inclined to invest in a NoSQL database, businesses must holistically evaluate their application requirements.  

Final Thoughts 

If you only need a managed solution for database instances, RDS is a better choice to use existing applications or architectural models with minimal changes.  

If you’re looking for low-latency responses to high-volume queries and use AWS as the primary cloud environment, DynamoDB is a better choice.  

Schedule a call with our solution architects to help you find the best fit for your organization.        

 

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Top 5 AWS Monitoring and Optimization Tools

 

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