Costs

If you’ve been using Amazon DynamoDB for a while, you’ve probably noticed something: not all your data gets the same attention. Some of it is “hot” — frequently accessed, constantly updated. But a lot of it is “cold” — just sitting there, costing you money every month.

What if you could store that cold data somewhere cheaper without changing your code or losing availability?

That’s exactly what DynamoDB Standard-IA (Infrequent Access) is for. In this post, we’ll break down what it is, how it works, how it can save you money, and when it might not be the best idea.

Recap on previous post:

• AWS: DynamoDB & DAX Cost Factors
• AWS: DynamoDB Basics

DynamoDB Table Classes

DynamoDB offers different table classes to optimize costs based on your access patterns:

1. Standard – For data you access frequently.
   • Designed for low-latency access any time.
   • Best for your main, active application data.
   • The default table class when you create a new DynamoDB table.
   • Suitable for most workloads. Provides high availability and durability.
2. Standard-IA (Infrequent Access) – For data you rarely read or write.
   • Designed for data that is not accessed often but needs to be available when needed.
   • Offers lower storage costs compared to Standard.
   • Higher retrieval costs, so it’s best for data that you access less than once a month.

Both table classes work exactly the same way from a developer’s point of view:

• Same APIs
• Same queries
• Same AWS Console experience

The only difference? How AWS stores it behind the scenes and how much you pay.

What is Standard-IA?

Standard-IA is a table class designed for data that you access infrequently. It’s like a storage locker for your cold data — it’s still there when you need it, but it costs less to keep it around.

Think of it like moving your old books to a basement shelf:

• They’re still yours.
• You can still get them any time.
• But they’re not taking up expensive prime shelf space.

How can it save you money?

The main savings come from storage pricing:

Storage Class	Price per GB/month
Standard	~$0.25
Standard-IA	~$0.10

That’s about 60% cheaper for storage.

Example: If you have 100 GB of archived order history:

• Standard = ~$25/month
• Standard-IA = ~$10/month

💡 That’s $15/month saved — or $180/year — just for one table.

The Catch

But it’s not all sunshine and rainbows. There are some important trade-offs to consider:

• Retrieval Costs – Around $0.01 per GB each time you read data from IA.
• Minimum 30-Day Storage Billing – You pay for at least 30 days even if you delete earlier.
• Not for Hot Data – If accessed often, retrieval fees can eat up savings.
• Whole-Table Setting – You can’t mix Standard and IA in one table.

Best Practice before Switching

• Check Access Patterns — Use CloudWatch metrics to see how often the table is read.
• Move Predictable Cold Data — Avoid sudden spikes in retrieval.
• Test on a Smaller Table First — See if retrieval costs are low enough to justify the switch.
• Combine With TTL — Automatically delete expired data to save more.

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DynamoDB Standard-IA is like a budget-friendly storage locker for data you still need but rarely touch. It can cut storage costs by more than half — but only if you choose the right workloads.

Rule of thumb: If it’s predictable, cold, and still worth keeping — IA is your friend.

We discussed about DynamoDB in previous post, but let’s dive deeper into the cost factors associated with DynamoDB and its accelerator, DAX (DynamoDB Accelerator).

Recap

• Amazon DynamoDB (DDB) is AWS’s fully managed NoSQL database service, designed for applications that require consistent performance at any scale.

• Amazon DynamoDB Accelerator (DAX) is an in-memory caching service for DynamoDB. Think of it as a turbocharger — it reduces read latency from milliseconds to microseconds by storing frequently accessed data in memory.

Together, DDB and DAX can significantly improve application performance — but they also come with different cost models you’ll want to understand before adopting.

When to Use DAX?

DAX is particularly useful when:

• Your workload has high read traffic with repeated queries for the same items.
• You want microsecond read latency for real-time user experience.
• You aim to offload read traffic from DynamoDB to reduce provisioned read capacity usage.

Example: A database for AI model training, where the same training data is accessed repeatedly.

Skip DAX when:

• Your workload is write-heavy with low read repetition.
• Your queries are strongly consistent (DAX only supports eventually consistent reads).
• Your access patterns are highly dynamic and unpredictable — the cache hit rate might be low.

Understanding DynamoDB Costs

DynamoDB costs come from three main areas:

• Reading Data
  • Imagine a reading allowance — every time you check a page from a book, it uses part of your allowance.
  • You can either pay per read (On-Demand) or buy a monthly “reading subscription” (Provisioned) if you know your usual usage.
• Writing Data
  • Adding or updating books also uses an allowance — think of it as your “writing subscription” or “per-write” payment.
• Storing Data
  • This is your bookshelf space.
  • Regular storage (Standard) is always ready but costs more.
  • Cheaper storage (Standard-IA) is for books you rarely read, but you’ll pay a small fee each time you take one.

Extras You Might Pay For:

• Backups — like taking daily photos of your bookshelf.
• Copies in other regions — like having the same library in multiple cities.

Understanding DAX Costs

5. DAX Costs DAX pricing is per node-hour, depending on node type:

• Smallest node (dax.t3.small) is the cheapest, suitable for dev/test.
• Larger nodes (dax.r5.large, etc.) cost more but handle higher throughput.
• DAX clusters require at least 3 nodes for fault tolerance in production.

Note: DAX charges are separate from DynamoDB — even if your reads come from the cache.

Cost Comparison

Component	Without DAX (Provisioned)	With DAX (Provisioned)
Read Capacity Cost	High (due to all reads hitting DDB)	Lower (fewer RCUs needed)
Write Capacity Cost	Same	Same
Storage Cost	Same	Same
DAX Cost	$0	Node-hour charges

If your cache hit rate is low, DAX might increase costs without much benefit.

Final Thoughts

• Use DAX if you have heavy, repeated reads and need lightning-fast results.
• Use Standard-IA storage for rarely accessed data — but don’t forget the retrieval cost.
• Always measure first: monitor read/write usage and cache hit rates before committing.