The Good Tech Companies - A Better Way to Estimate DynamoDB Costs

Episode Date: July 21, 2025

This story was originally published on HackerNoon at: https://hackernoon.com/a-better-way-to-estimate-dynamodb-costs. Discover a better way to estimate DynamoDB costs with a new analyzer that models real-world workloads, peak traffic, and cost scenarios more accurately. Check more stories related to cloud at: https://hackernoon.com/c/cloud. You can also check exclusive content about #dynamodb-cost-analyzer, #dynamodb-pricing, #aws-dynamodb-calculator, #dynamodb-cost-estimation, #scylladb-calculator, #dynamodb-workload-costs, #cloud-database-pricing, #good-company, and more. This story was written by: @scylladb. Learn more about this writer by checking @scylladb's about page, and for more stories, please visit hackernoon.com. DynamoDB costs often surprise teams due to unpredictable workloads and AWS calculator limitations. ScyllaDB created a new cost analyzer that factors in real-world scenarios like bursty traffic, peaks, and global tables. Built as a simple client-side tool, it enables developers to explore “what-if” cost scenarios and better understand their true DynamoDB expenses.

This audio is presented by Hacker Noon, where anyone can learn anything about any technology. A Better Way to Estimate DynamoDB Costs by SillyDB We built a new DynamoDB cost analyzer that helps developers understand what their workloads will really cost DynamoDB costs can blindside you. Teams regularly face, bill shock. That sinking feeling when you look at a shockingly high bill and realize that you haven't paid enough attention to your usage, especially with on-demand pricing. Provisioned capacity brings a different risk, performance. If you can't accurately predict capacity or your math is off, requests get throttled. It's a delicate balancing act. Although AWS offers a DynamoDB pricing calculator, it often misses the nuances of real-world workloads, e.g.

bursty traffic or uneven access patterns, orcing global tables or caching. We wanted something better. In full transparency, we wanted something better to help the teams considering SillyDB as a DynamoDB alternative. So we built a new DynamoDB cost calculator that helps developers understand what their workloads will really cost. Although we designed it for teams comparing DynamoDB with Ciladb, we believe it's useful for anyone looking to more accurately estimate their DynamoDB costs, for any reason. You can see the live version at, calculator, Ciladb, com how we built it, we wanted to build something that would work client side, without the need for any server components. It's a simple JavaScript single page application that we currently host on

GitHub pages. If you want to check out the source code, feel free to take a look at https://github.com SillyDB Calculator to be honest, working with the examples at https://calculator. honest, working with the examples at https:// calculator. Oz was a bit of a nightmare, and when you, show calculations, you get these walls of text. I was tempted to take a shorter approach, like, monthly WCU cost equals WCUs times price underscore per underscore WCU underscore per underscore hour times 730 hours,. But every time I simplified this, I found it harder to get parity between what I calculated in the final price in AWS's calculation.

Sometimes the difference was due to rounding. Other times it was due to the mixture of reserved plus provision capacity and so on. So to make it easier for me to debug, I faithfully followed their calculations line by line and tried to replicate this in my own rather ugly function https colon slash slash github com siladibi

calculator blob main src calculator Jsi may still refactor this into smaller functions, but for now I wanted to get parity between theirs and ours You'll see that there are also some end-to-end tests for these calculations. I use those to test for a bunch of different configurations. I will probably expand on these in time as well. So that gets the job done for on-demand, provisioned, and reserved capacity models. If you've used AWS's calculator, you know that you can't specify things like a peak, or peak width, in on-demand. I'm not sure about their reasoning. I decided it would be easier for users to

specify both the baseline and peak for reads and writes, respectively, in on demand, much like provisioned capacity. Another design decision was to represent the traffic using a chart. I do better with visuals, so seeing the peaks and troughs makes it easier for me to understand, and I hope it does for you as well. You'll also notice that as you change the inputs, the URL query parameters change to reflect those inputs. That's designed to make it easier to share and reference specific variations of costs.

There's some other math in there, like figuring out the true cost of global tables and understanding derived costs of things like network transfer or DynamoDB Accelerator, DAX. However, explaining all that is a bit too dense for this format. We'll talk more about that in an upcoming webinar, see the next section. The good news is that you can estimate these costs in addition to your workload, as they can be big cost multipliers when planning out your usage of DynamoDB. Explore, what if, scenarios for your own workloads analyzing costs in real-world scenarios. The ultimate goal of all this tinkering and tuning is to help you explore various what-if scenarios from a DynamoDB cost perspective.

To get started, we're sharing the cost impacts of some of the more interesting DynamoDB user scenarios we've come across at Silidibi. My colleague Gui and I just got together for a deep dive into how factors like traffic surges, multi-data center expansion, and the introduction of caching, e.g. DAX, impact DynamoDB costs. We explored how a few, anonymized, teams we work with ended up blindsided by their DynamoDB bills and the various options they considered for getting costs back under control. Watch the DynamoDB costs chat now about Tim Coop Montz Tim has had his hands in all forms

of engineering for the past couple of decades with a penchant for reliability and security. In 2013 he founded Flood.io, a distributed performance testing platform. After it was acquired, he enjoyed scaling the product, business and team before moving on to other performance-related endeavors. Thank you for listening to this Hacker Noon story, read by Artificial Intelligence. Visit hackernoon.com to read, write, learn and publish.