The Good Tech Companies - Why DynamoDB Costs Explode

Episode Date: November 17, 2025

This story was originally published on HackerNoon at: https://hackernoon.com/why-dynamodb-costs-explode. Discover how DynamoDB’s pricing quirks—rounding, replication, caching, and global tables—can skyrocket costs, and how ScyllaDB offers predictable pricing. Check more stories related to cloud at: https://hackernoon.com/c/cloud. You can also check exclusive content about #dynamodb-costs, #aws-dynamodb-pricing, #dynamodb-global-tables, #dynamodb-vs-scylladb, #dax-caching-cost, #dynamodb-cost-calculator, #cloud-database-optimization, #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’s per-operation billing model hides costly pitfalls: rounded-up reads/writes, global table replication, DAX caching, and auto-scaling inefficiencies. Real-world cases show costs ballooning into millions due to inefficiencies. ScyllaDB’s predictable pricing and built-in caching help teams cut costs, improve performance, and regain control.

This audio is presented by Hacker Noon, where anyone can learn anything about any technology. Why DynamoDB costs explode by SkyloDB. Why real-world DynamoDB usage scenarios often lead to unexpected expenses in my last post on DynamoDB costs. I covered how unpredictable workloads lead to unpredictable costs in DynamoDB. Now let's go deeper. Once you've understood the basics, like the Nutty 7, 5x inflation of on-demand compared to reserved or the excessive costs around item size, replication and caching, you'll realize that DynamoDB costs aren't just about read, write volume. It's a lot more nuanced in the real world. Round them up, a million rights per second at 100 bytes isn't in the same galaxy as a million rights at 5 kilobytes. Why? Because Dynamody B

meters out the costs in rounded up 1kb chunks for writes and 4 kilobytes for reeds. Writing a 1, 2 kilobytes item, you're billed for 2kb. Reading a 4, 5 kilobytes item with strong consistency? You get charged for 8 kilobytes. You're not just paying for what you use, you're paying for rounding up. Remember this character in Superman 3 taking one half a cent from each paycheck? It's the Samadil, and yes, $85,789. 90 was a lot of money in 1983. Wasted capacity is unavoidable at scale, but it becomes very real, very fast when you cross that boundary on every single operation. And don't forget thathered cap of 400 kilobytes per item. That's not a pricing issue directly, but it's something that has motivated DynamoDB

customers to look at alternatives. Our Dynamody B cost calculator lets you model all of this. What it doesn't account for are some of the real-world landmines, like the fact that a conflict resolved right, such as concurrent updates in multiple regions, still costs you for each attempt, even if only the last right wins. Or when you build your OWNTL expiration logic, maybe pulling a bunch of items in a scan, checking timestamps in app code, or issuing deletes. All that data transfer and, replicated, write, delete activity adds up fast, even though you're trying to clean up. We discussed these tricky situations in detail in a recent DynamoDB costs

webinar, which you can now watch on demand. Global tables are a global pain, so you want low latency for users worldwide? Global tables are the easiest way to do that. Some might even say that it's batteries included, but those batteries come with a huge price tag. Every right gets duplicated across additional regions. Write a three, five kilobytes item and replicated to four regions? Now you're paying for four by four kilobytes, rounded up, of course. Don't forget to tack on inter-region network transfer. That's another hit at premium pricing. And sorry, you cannot reserve those replicated rights either. You're paying for that speed, several times over, and the bill scales linearly with your regional growth. It gets worse when multiple regions write to the same item

concurrently. Dynamody B resolves the conflict. Last right wins, but you still pay for every attempt. Losing rights still charge. Our cost calculator lets you model all this. We use conservative prices for us east, but the more exotic the region, the more likely the costs will be higher. As an Australian, your pain, so have a think about that batteries included global tables replication cost, and please remember, it's per table, Dax caching with a catch. Now do you want even tighter read latency, especially for your latency-sensitive P99? DynamoDB accelerator, Dax, helps, but it adds overhead, both operational and financial. Clusters need to be sized right, hit ratios tuned, and failover cases handled in your application. Miss the cash, pay for the read, fail to update,

the cache, risk stale data. Even after you have tuned it, it's not free. Dax instances are billed by the hour, at a flat rate, and once again, without reserved instance options like you might be accustomed to. Our DynamoDB cost calculator lets you simulate cash hit ratios, data set sizes, instance types, and nodes. It won't predict cash efficiency, but it will help you catch those cash gotches. Multi-million dollar recommendation engine. A large streaming service built a global recommendation engine with DynamoDB. Daily batch jobs generate fresh recommendations and write them to a one petabyte single table, replicated across six regions. They optimized for latency and local rights, the cost, every right to the bastable plus five replicated rights. Every user interaction triggered a

write, watch history, feedback, preferences. And thanks to that daily refresh cycle, they were rewriting the table, whether or not anything change. They used provision capacity, scaling up for for anticipated traffic spikes, but still struggled with latency. Cash hit rates were too low to make Redis or DAX cost effective. The result, base workload alone cost tens of millions per year, and the total doubled after accommodating peaks in traffic spikes and batch load processes. For many teams, that's more than the revenue of the product itself. So, they turned to Skylidibi.

After they switched to our pricing model based on provision capacity, not per operation billing, Skyladyby was able to significant compress their data stored, while also improving network compression between AZs and regions. They had the freedom to do this on any cloud, or even on premise. They slashed their costs, improved performance, and removed the need to over-provision for spikes. Daily batch jobs run faster and their business continues to scale without their database build doing the same. Another case of caching to survive, an AT-tech company using DynamoDB ran into cash complexity the hard way. They deployed 48 Dax nodes across four regions to hit their P99 latency targets.

Each node is tailored to that region's workload, after a lot of trial and error. Their rights, 246 bytes, item, were wasting 75% of the right unit build. Their analytics workload tanked live traffic during spikes, and perhaps worst of all, auto-scaling triggers just weren't fast enough, resulting in request throttling and application failures. The total DynamoDB in DAX cost was hundreds of thousands per year. SkyladyB offered a much simpler solution. Built-in row caching used instance memory at no extra cost with no external caching layer to maintain. They also earn their analytics and OLTP workload side by side using workload prioritization with no hit to performance. Even better, their TTL-based

session expiration was handled automatically without extra read, delete logic. Cost and complexity dropped. and they're now a happy customer. Watch the Dynamody B costs video. If you missed the webinar, be sure to check out the Dynamody B costs video, especially where Guillermo covers all these real-world workloads in detail. Key takeaways. DynamoDi B costs are non-linear and shaped by usage patterns, not just throughput. Global tables, item size, conflict resolution, cash warm-up and more can turn, reasonable,

usage into a seven-figure nightmare. Dax and auto-scaling aren't magic. They need tuning and still cost significant money to get right. Our DynamoDB cost calculator helps model these hidden costs and compare different setups, even if you're not using Skyladyby. And finally, if you're a team with unpredictable costs and performance using DynamoDB, make the switch to Skyladyby and enjoy the benefits of predictable pricing, built-in efficiency and more control over your database architecture.

If you want to discuss the nuances of your specific use case and get your technical questions answered, chat with us here. About T.I.M. Kube Mont's 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 I.O. A distributed performance testing platform. After it was acquired, he enjoyed at scaling the product, business and team before moving on to other performance-related endeavors. Thank you for listening to this Hackernoon story, read by artificial intelligence. Visit hackernoon.com to read, write, learn and publish.