10 things to keep in mind when working with DynamoDB - 2022
Tags: dynamodb, backend, serverless, aws
Published: 2023-01-03 00:39:43

---
title: 10 things to keep in mind when working with DynamoDB - 2022
published: true
date: 2023-01-02 19:20:00 UTC
tags: DynamoDB,Backend,Serverless,AWS
canonical_url: https://techdevblog.io/10-things-to-keep-in-mind-when-working-with-dynamodb-2022/
---

 ![10 things to keep in mind when working with DynamoDB - 2022](https://techdevblog.io/content/images/2023/01/image_3.png)

[DynamoDB](https://aws.amazon.com/dynamodb/) is a popular NoSQL database service offered by Amazon Web Services (AWS). It's known for its scalability, reliability, and low latency, making it a great choice for a wide range of applications. However, as with any database, there are a few things that developers working with [DynamoDB](https://aws.amazon.com/dynamodb/) should be careful of. In this article, we'll take a look at the top 10 things any developer working with [DynamoDB](https://aws.amazon.com/dynamodb/) should be careful of.

# Provisioned throughput

One thing to be careful of when working with [DynamoDB](https://aws.amazon.com/dynamodb/) is provisioned throughput. [DynamoDB](https://aws.amazon.com/dynamodb/) allows you to specify the amount of read and write capacity that you need for your table, in the form of read capacity units and write capacity units. If you exceed the provisioned throughput for your table, you may experience latency issues or even request throttling. It's important to carefully monitor your provisioned throughput and adjust it as needed to ensure the best performance for your application.

# Data modeling

Data modeling is another important consideration when working with [DynamoDB](https://aws.amazon.com/dynamodb/). [DynamoDB](https://aws.amazon.com/dynamodb/) is a NoSQL database, which means that it does not have the same data modeling capabilities as a traditional relational database. This can make it challenging to model your data in a way that is efficient and flexible. It's important to carefully consider your data model and how it will be used by your application to ensure the best performance and flexibility. This is where Alex Debrie's [DynamoDB Guide](https://www.dynamodbguide.com/) and [DynamoDB Book](https://www.dynamodbbook.com) come in handy!

# Partition keys and sort keys

[DynamoDB](https://aws.amazon.com/dynamodb/) uses partition keys and sort keys to determine how data is stored and retrieved in a table. It's important to carefully consider your partition keys and sort keys to ensure that your data is evenly distributed and can be retrieved efficiently.

# Scaling

Scaling is another important consideration when working with [DynamoDB](https://aws.amazon.com/dynamodb/). [DynamoDB](https://aws.amazon.com/dynamodb/) is designed to scale automatically, but it's important to carefully monitor your usage and adjust your provisioned throughput as needed to ensure the best performance. Or use [DynamoDB On-Demand scaling](https://aws.amazon.com/blogs/aws/amazon-dynamodb-on-demand-no-capacity-planning-and-pay-per-request-pricing/). It's also important to consider the impact of scaling on your data model and how it may affect your application.

# Data types

[DynamoDB](https://aws.amazon.com/dynamodb/) supports a wide range of data types, including scalar types, set types, and document types. It's important to carefully consider which data types are best suited for your data and how they will be used by your application. Choosing the wrong data types can lead to performance issues or even data loss.

# Secondary indexes

Secondary indexes can be a useful tool for querying and retrieving data from [DynamoDB](https://aws.amazon.com/dynamodb/), but it's important to be careful when using them. Secondary indexes can impact the performance of your table and can increase the cost of your provisioned throughput. It's important to carefully consider whether you really need a secondary index and, if so, to design it carefully to ensure the best performance and cost efficiency.

# Streams

[DynamoDB](https://aws.amazon.com/dynamodb/) streams can be a useful tool for real-time data processing, but it's important to be careful when using them. Streams can impact the performance of your table and can increase the cost of your provisioned throughput. It's important to carefully consider whether you really need a stream and, if so, to design it carefully to ensure the best performance and cost efficiency.

# Backup and restore

[DynamoDB](https://aws.amazon.com/dynamodb/) allows you to create backups of your data and restore it if necessary. It's important to be careful when working with backups and restores, as they can impact the performance of your table and may incur additional costs. It's important to carefully consider your backup and restore strategy and to test it regularly to ensure that it works as expected.

# Security

Security is an important consideration when working with any database, including [DynamoDB](https://aws.amazon.com/dynamodb/). It's important to be careful when working with sensitive data and to follow best practices for security, such as using encryption and implementing access controls.

# Costs

Finally, it's important to be careful of costs when working with [DynamoDB](https://aws.amazon.com/dynamodb/). [DynamoDB](https://aws.amazon.com/dynamodb/) charges for both provisioned throughput and data storage, and it's important to carefully monitor your usage and adjust your provisioned throughput as needed to ensure that you don't incur unexpected costs. It's also important to consider the long-term cost of your data model and how it may impact your overall costs.

# Conclusion

In conclusion, these are the top 10 things any developer working with [DynamoDB](https://aws.amazon.com/dynamodb/) should be careful of. By being aware of these considerations, you can help ensure that your [DynamoDB](https://aws.amazon.com/dynamodb/) implementation is efficient, reliable, and cost-effective.