Reducing Your Database Hosting Costs: DigitalOcean vs. AWS vs. Azure

If you’re hosting your databases in the cloud, choosing the right cloud service provider is a significant decision to make for your long-term hosting costs. This is especially apparent in today's world where organizations are doing whatever they can to optimize and reduce their costs. Over the last few weeks, we have been inundated with requests from SMB customers looking to improve the ROI on their database hosting. In this article, we are going to compare three of the most popular cloud providers, AWS vs. Azure vs. DigitalOcean for their database hosting costs for MongoDB® database to help you decide which cloud is best for your business.

Comparing Cloud Instance Costs

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How to Improve MySQL AWS Performance 2X Over Amazon RDS at The Same Cost

AWS is the #1 cloud provider for open-source database hosting, and the go-to cloud for MySQL deployments. As organizations continue to migrate to the cloud, it’s important to get in front of performance issues, such as high latency, low throughput, and replication lag with higher distances between your users and cloud infrastructure. While many AWS users default to their managed database solution, Amazon RDS, there are alternatives available that can improve your MySQL performance on AWS through advanced customization options and unlimited EC2 instance type support. ScaleGrid offers a compelling alternative to hosting MySQL on AWS that offers better performance, more control, and no cloud vendor lock-in and the same price as Amazon RDS. In this post, we compare the performance of MySQL Amazon RDS vs. MySQL Hosting at ScaleGrid on AWS High Performance instances.

TLDR

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7 Not So Sexy Tips for Saving Money On Amazon

Harish Ganesan CTO of 8KMiles has a very helpful blog, Cloud, Big Data and Mobile, where he shows a nice analytical bent which leads to a lot of practical advice and cost saving tips:

1. Use SQS Batch Requests to reduce the number of requests hitting SQS which saves costs. Sending 10 messages in a single batch request which in the example save $30/month.
2. Use SQS Long Polling to reduce extra polling requests, cutting down empty receives, which in the example saves ~$600 in empty receive leakage costs.
3. Choose the right search technology choice to save costs in AWS by matching your activity pattern to the technology. For a small application with constant load or a heavily utilized search tier or seasonal loads Amazon Cloud Search looks like the cost efficient play. 
4. Use Amazon CloudFront Price Class to minimize costs by selecting the right Price Class for your audience to potentially reduce delivery costs by excluding Amazon CloudFront’s more expensive edge locations.
5. Optimize ElastiCache Cluster costs by right sizing cluster node sizes. For different usage scenarios (heavy, moderate, low) their are optimal instances types. Choosing the right type for the right usage scenario saves money.
6. Amazon Auto Scaling can save costs by better matching demand and capacity. Certainly not a new idea but the diagrams, different leakage scenarios (daily spike, weekly fluctuation, seasonal spike), and the explanation of potential savings (substantial) are well done.
7. Use Amazon S3 Object Expiration feature to delete old backups, logs, documents, digital media, etc. A leakage of ~20 TB adds up to a tidy ~1650 USD a year.