DynamoDB Cost Optimization: A Practical Guide to Cutting Your Bill 💰

DynamoDB's performance is legendary—single-digit millisecond latency at any scale. But its pricing model can surprise you if you're not paying attention. Teams often adopt DynamoDB for speed and scalability, then discover months later that their monthly bill has grown well beyond expectations. The good news? With the right strategies, you can significantly reduce DynamoDB costs without sacrificing performance. Let's walk through the most impactful optimizations. 🧭

Greg Krumm

Published Jun 10, 2026

Last modified Jun 10, 2026

📊 Understanding the Cost Levers

DynamoDB costs come from four main areas. Knowing which lever to pull is half the battle:

Cost Component	What Drives It
💡 Read/Write capacity	How many requests your application makes (and which capacity mode you're using)
💾 Storage	Total data stored, including GSI replicated data
🔍 GSI throughput	Each GSI consumes its own read/write capacity
📦 Features	Backups, PITR, Streams, data transfer, and exports

For a full breakdown, see the DynamoDB on-demand pricing and provisioned pricing pages.

1️⃣ Choose the Right Capacity Mode

This is the single biggest cost decision you'll make. DynamoDB offers two modes:

On-demand mode — Pay per request. No capacity planning needed. Best for unpredictable or spiky workloads. AWS recently cut on-demand pricing by 50% , making it even more competitive.
Provisioned mode — You specify read/write capacity units (RCUs/WCUs) per second. Best for steady, predictable workloads. Combine with auto-scaling to handle traffic variations.

The rule of thumb: If your traffic is predictable and steady, provisioned mode with auto-scaling can save you 50–70% compared to on-demand. If your traffic is bursty or unpredictable, on-demand avoids over-provisioning waste. See the throughput strategy guide for a detailed comparison.

2️⃣ Use Standard-IA for Cold Data

If storage makes up more than 50% of your table's monthly cost, switch to the Standard-IA table class . It offers ~60% lower storage costs with ~25% higher read/write costs—a great tradeoff for tables with lots of data that's rarely accessed.

Good candidates for Standard-IA:

📜 Application logs and audit trails
🛒 Old order history
🎮 Past gaming achievements
📱 Archived user sessions

You can switch table classes with zero downtime—no migration required.

3️⃣ Optimize Your GSIs

GSIs are one of the sneakiest cost drivers. Every GSI replicates data from your base table, consuming its own storage and write capacity. Here's how to keep them lean:

Use KEYS_ONLY or INCLUDE projections instead of ALL. Projecting all attributes doubles your storage cost per GSI.
Delete unused GSIs. Audit your GSIs regularly—if your application no longer queries an index, remove it.
Consolidate GSIs with the new multi-key composite keys. The recently launched multi-attribute GSI keys can replace multiple GSIs with a single, more flexible one.

4️⃣ Implement TTL for Data Lifecycle

Time to Live (TTL) automatically deletes expired items at no cost—no write capacity consumed. If your data has a natural expiration (sessions, temporary tokens, time-limited offers), TTL is free cleanup.

5️⃣ Right-Size Your Items

DynamoDB charges per read/write capacity unit, and unit consumption is based on item size. Smaller items = fewer capacity units = lower costs.

Remove attributes you don't need at query time
Compress large string values before storing
Store large objects (images, documents) in S3 and keep only a reference in DynamoDB
Use shorter attribute names for high-volume tables (every byte counts at scale)

6️⃣ Use Reserved Capacity for Predictable Workloads

If you're on provisioned mode with steady traffic, you have two commitment-based options:

Database Savings Plans (recommended for most teams) — Launched at re:Invent 2025, these let you commit to a consistent hourly spend (measured in $/hour) over a 1-year term with no upfront payment and save up to 35%. The big advantage? They're flexible across DynamoDB, Aurora, RDS, ElastiCache, DocumentDB, Neptune, Keyspaces, and Timestream — so if your NoSQL usage shifts between services, the discount follows. No need to predict exactly which table or capacity mode you'll use.

Reserved Capacity (for DynamoDB-specific high-volume) — The legacy option offering up to 77% savings for 1-year or 3-year commitments, but locked to specific regions and capacity amounts. Best when you have large, predictable DynamoDB-only workloads and are confident they won't shift.

Which should you pick? Start with Database Savings Plans unless you have very large, stable DynamoDB-only workloads where the deeper reserved capacity discount justifies the rigidity. For teams using multiple AWS database services, Savings Plans are a no-brainer — one commitment covers your whole NoSQL portfolio.

For more details, see the Database Savings Plans blog post and the Savings Plans FAQ .

⚡ Quick Wins Checklist

Review capacity mode: on-demand vs provisioned with auto-scaling
Check if any tables qualify for Standard-IA (storage > 50% of cost)
Audit GSI projections—switch from ALL to INCLUDE or KEYS_ONLY
Enable TTL on tables with expiring data
Remove unused GSIs
Consider reserved capacity for stable workloads

For a deeper dive, see the DynamoDB cost optimization documentation and the Standard-IA blog post .

👉 Want to share your cost optimization wins (or stories)? Join us in the AWS NoSQL Launchpad Space on Builder Center where we break down DynamoDB design patterns, share real-world strategies, and learn the NoSQL mindset together—one use case at a time.

# nosql # cost # cost-optimization # cost-savings # amazon-dynamodb

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