AWS DynamoDB with C#: A Complete .NET Tutorial (2026)

Learn how to use AWS DynamoDB with C# in .NET. Step-by-step tutorial with code examples, best practices, and serverless tips. Start building today!

If you are building serverless or cloud-native applications, learning how to use AWS DynamoDB with C# is one of the most valuable skills you can add to your .NET toolkit. DynamoDB is Amazon’s fully managed NoSQL database that delivers single-digit millisecond latency at any scale, and it pairs perfectly with .NET workloads running on AWS Lambda, ECS, or EC2. In this DynamoDB C# tutorial, you will learn how to connect, model data, and run CRUD operations using the AWS SDK for .NET — plus the best practices and common pitfalls that trip up most developers.

By the end, you will understand not just how to call DynamoDB from C#, but why the API is designed the way it is, so you can make smart decisions in production.

Why Use AWS DynamoDB with C# and .NET?

Relational databases like SQL Server are excellent for normalized, relational data with complex joins. But for high-throughput, horizontally scalable workloads — think user sessions, shopping carts, IoT telemetry, gaming leaderboards, or event logging — a NoSQL database is often a better fit. Here is why DynamoDB shines for serverless .NET applications:

• Fully managed: No servers to patch, no replicas to configure. AWS handles availability and durability across multiple Availability Zones.
• Predictable performance: Single-digit millisecond reads and writes regardless of table size.
• Serverless-friendly: On-demand capacity mode means you pay per request — ideal for spiky AWS Lambda workloads with no idle cost.
• Auto-scaling: DynamoDB scales throughput up and down automatically, so you never provision for peak and pay for it 24/7.

Because DynamoDB charges for read/write capacity rather than CPU time, it complements the per-invocation billing model of serverless functions almost perfectly.

Setting Up the AWS SDK for .NET

To talk to DynamoDB from C#, you need the AWS SDK for .NET. The relevant NuGet package is AWSSDK.DynamoDBv2. Install it via the .NET CLI:

// Run in your terminal
// dotnet add package AWSSDK.DynamoDBv2

using Amazon;
using Amazon.DynamoDBv2;
using Amazon.DynamoDBv2.DataModel;
using Amazon.DynamoDBv2.DocumentModel;
using Amazon.DynamoDBv2.Model;

The SDK resolves credentials automatically using the default credential chain: environment variables, shared ~/.aws/credentials files, or — best of all in production — IAM roles attached to your Lambda function or EC2 instance. Never hard-code AWS access keys in your source code.

Creating the client is straightforward:

// The client picks up credentials from the default chain automatically
var client = new AmazonDynamoDBClient(RegionEndpoint.USEast1);

Three Programming Models You Should Know

One thing that confuses newcomers to AWS DynamoDB in C# is that the SDK exposes three distinct APIs, layered from low-level to high-level:

• Low-level API (AmazonDynamoDBClient): Full control, but verbose. You work with AttributeValue dictionaries.
• Document model (Table, Document): A middle ground using flexible JSON-like documents.
• Object persistence model (DynamoDBContext): An ORM-style mapper that turns C# classes into DynamoDB items. This is the most productive for most apps.

We will focus on the object persistence model with DynamoDBContext, then show the low-level API for queries that need precision.

Modeling Data: Mapping a C# Class to a DynamoDB Table

DynamoDB tables require a primary key, which is either a single partition key (hash key) or a composite of a partition key plus a sort key (range key). Choosing the right key is the single most important design decision in DynamoDB, because it determines how data is distributed and queried.

Here is a Product class decorated with DynamoDB attributes:

[DynamoDBTable("Products")]
public class Product
{
    [DynamoDBHashKey]                 // Partition key
    public string Category { get; set; }

    [DynamoDBRangeKey]                // Sort key
    public string ProductId { get; set; }

    [DynamoDBProperty]
    public string Name { get; set; }

    [DynamoDBProperty]
    public decimal Price { get; set; }

    [DynamoDBProperty]
    public int StockCount { get; set; }

    [DynamoDBProperty("tags")]       // Custom attribute name
    public List Tags { get; set; }
}

With Category as the partition key and ProductId as the sort key, you can efficiently fetch all products in a category, sorted by their ID — without scanning the whole table.

CRUD Operations: A Complete DynamoDB C# Example

Now let’s run the four core operations. First, wrap the client in a DynamoDBContext:

var client = new AmazonDynamoDBClient(RegionEndpoint.USEast1);
var context = new DynamoDBContext(client);

Create and Update (SaveAsync)

In DynamoDB, writing an item that already exists overwrites it. The same SaveAsync method handles both insert and update — this is an “upsert” by default.

var product = new Product
{
    Category = "Electronics",
    ProductId = "PROD-1001",
    Name = "Wireless Headphones",
    Price = 79.99m,
    StockCount = 120,
    Tags = new List { "audio", "bluetooth" }
};

await context.SaveAsync(product);
Console.WriteLine("Product saved.");

Read (LoadAsync)

To read a single item, supply the full primary key. Because we have a composite key, you must pass both the partition key and the sort key:

var item = await context.LoadAsync("Electronics", "PROD-1001");

if (item != null)
{
    Console.WriteLine($"{item.Name} costs {item.Price:C}");
}

Delete (DeleteAsync)

await context.DeleteAsync("Electronics", "PROD-1001");
Console.WriteLine("Product deleted.");

Query vs. Scan: The Most Important Performance Lesson

This is where many developers learning AWS DynamoDB with C# make costly mistakes. DynamoDB offers two ways to retrieve multiple items, and they are not interchangeable:

• Query — reads items by partition key (and optionally filters on the sort key). It is fast and only reads the items you target.
• Scan — reads every item in the table, then filters. It is slow and expensive on large tables.

Rule of thumb: use Query whenever possible and avoid Scan in production code paths. A Scan on a million-item table consumes read capacity for all million items even if you only want ten of them.

Here is an efficient query that fetches all electronics priced above a threshold using the object persistence model:

var query = context.QueryAsync(
    "Electronics",                                  // Partition key value
    new DynamoDBOperationConfig
    {
        QueryFilter = new List
        {
            new ScanCondition("Price", ScanOperator.GreaterThan, 50.00m)
        }
    });

var results = await query.GetRemainingAsync();

foreach (var p in results)
{
    Console.WriteLine($"{p.Name}: {p.Price:C}");
}

Note that the query targets a single partition ("Electronics") first, so DynamoDB reads only that partition. The price condition is applied as a filter after the key match — filters reduce the data returned, not the data read, so design your keys so the partition itself is selective.

Low-Level Query with Expression Attributes

For maximum control — for example, paginating with LastEvaluatedKey — drop to the low-level API:

var request = new QueryRequest
{
    TableName = "Products",
    KeyConditionExpression = "Category = :cat AND begins_with(ProductId, :prefix)",
    ExpressionAttributeValues = new Dictionary
    {
        [":cat"] = new AttributeValue { S = "Electronics" },
        [":prefix"] = new AttributeValue { S = "PROD-" }
    }
};

var response = await client.QueryAsync(request);
Console.WriteLine($"Found {response.Count} items.");

Best Practices for DynamoDB in .NET Applications

Following these best practices will save you money and prevent production headaches:

• Reuse the client. AmazonDynamoDBClient is thread-safe and expensive to create. Instantiate it once (as a singleton or a static field) and reuse it across requests. In ASP.NET Core, register it with the DI container via AddAWSService<IAmazonDynamoDB>().
• Use on-demand capacity for unpredictable traffic. It removes the need to forecast throughput and is ideal for serverless apps.
• Design single-table schemas. Advanced DynamoDB users often store multiple entity types in one table using composite keys and Global Secondary Indexes (GSIs) to minimize round trips.
• Use Global Secondary Indexes for alternate access patterns. If you need to query by an attribute that is not your primary key, create a GSI rather than resorting to a Scan.
• Batch your reads and writes. Use BatchGet and BatchWrite to handle up to 25 writes or 100 reads per call and reduce network overhead.
• Always handle ProvisionedThroughputExceededException. The SDK retries with exponential backoff automatically, but you should still design for throttling under load.

Common Pitfalls to Avoid

• Overusing Scan: The number one cause of high DynamoDB bills. Audit your code for ScanAsync calls.
• Hot partitions: If one partition key value gets disproportionate traffic (e.g., a single popular category), you create a throughput bottleneck. Distribute access by choosing high-cardinality partition keys.
• Forgetting eventual consistency: By default, reads are eventually consistent and may return slightly stale data. Pass a consistent-read option when you need the latest write.
• Storing huge items: DynamoDB items max out at 400 KB. Store large blobs in Amazon S3 and keep only a reference in DynamoDB.

Local Development with DynamoDB Local

You do not need a live AWS account to develop. DynamoDB Local runs in Docker and lets you test without incurring charges. Just point your client at it:

var config = new AmazonDynamoDBConfig
{
    ServiceURL = "http://localhost:8000"
};
var client = new AmazonDynamoDBClient("dummy", "dummy", config);

This makes your unit and integration tests fast, free, and isolated from production data.

Conclusion: Key Takeaways

Using AWS DynamoDB with C# unlocks a fully managed, infinitely scalable NoSQL database that fits serverless .NET applications like a glove. Here are the key takeaways from this tutorial:

• Install AWSSDK.DynamoDBv2 and prefer the high-level DynamoDBContext for productive CRUD operations.
• Choose your partition and sort keys carefully — they define your access patterns.
• Always favor Query over Scan to keep latency and costs low.
• Reuse a single thread-safe client, use on-demand capacity for spiky workloads, and reach for Global Secondary Indexes instead of scanning.
• Develop and test locally with DynamoDB Local before deploying to the cloud.

With these fundamentals and best practices, you are ready to build fast, cost-effective, serverless .NET applications on DynamoDB. Start small with a single table, measure your read/write capacity, and scale with confidence. Happy coding!

This article is part of the cloud and security guide (Azure, AWS, Google Cloud, infrastructure as code and security).