Amazon DynamoDB Accelerator (DAX) vs ElastiCache
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Amazon DynamoDB Accelerator (DAX) and ElastiCache both are fully managed caching services from AWS. DAX is designed especially for DynamoDB on the other hand ElastiCache can cache anything including DynamoDB.
So many times, we get confused especially while using DynamoDB on whether to go for DynamoDB DAX or ElastiCache as we think both can handle our caching needs.
In this post, we are going to learn about both of these offerings. After that, we’ll see the difference between Amazon DynamoDB Accelerator (DAX) and ElastiCache.
Alright? Lets get started …
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What is Amazon DynamoDB Accelerator (DAX)?
Amazon DynamoDB Accelerator also known as DAX is a fully managed in-memory cache for DynamoDB that takes the performance of your DynamoDB table to the next level.
DynamoDB itself usually performs in the range of single-digit milliseconds however using DAX with DynamoDB improves the performance to 10 times and provides a microsecond level of response time at any scale.
Now that’s amazing – isn’t it?
What is Amazon ElastiCache?
Amazon ElastiCache (Redis or Memcached) is a fully managed in-memory caching service that can enhance your application or database performance up to microsecond latency.
In other words, ElastiCache provides you with a managed way to deploy your Redis or Memcached cluster on AWS.
Instead of being specific like DAX is only for DynamoDB, ElastiCache works for pretty much everything like various databases or applications.
Let’s try to evaluate DynamoDB DAX and ElastiCache in terms of some import parameters.
Ease of Use: Amazon DynamoDB Accelerator (DAX) vs ElastiCache
As you know, to increase the read performance of your DynamoDB tables, you can use DAX as well as ElastiCache, let’s see which one is easier to use.
If you are already using DynamoDB, using DAX is super duper simple. All you need is to provision a DAX cluster and point your application to use a DAX client instead of DynamoDB. And, that’s all the code changes that you need to do. It’s hardly 1-3 lines. So migrating is super simple.
If you want to use ElastiCache, you need change your code heavily to implement the logic to leverage cache. For instance you will have to write logic to query cache first, if data is not found in cache then go to query DynamoDB and save the result back to cache to avoid any future cache miss. So literally you need to still do a lot of heavy lifting work including cache invalidation.
Performance: Amazon DynamoDB Accelerator (DAX) vs ElastiCache
Although both of them are fully managed caching services that promises to provide milliseconds of latency. There are evidences to prove that DynamoDB with DAX perform far better when you scale massively like millions of request per second.
Here is a good article that details the performance comparison and why it is worth switching to DynamoDB DAX from ElastiCache while using DynamoDB.
Link to the Article: https://medium.com/gumgum-tech/migrating-from-elasticache-for-memcached-to-dax-dynamodb-accelerator-ebc4677ee68e
Usecases: Amazon DynamoDB Accelerator (DAX) and ElastiCache
Although we know that they are cache and can be used for caching purpose. Lets see some of the usecases that fits them.
DynamoDB DAX Usecases
- Applications that are read-intensive and require faster response times in the range of microseconds.
- Some of the are gaming or trading applications
- If some items are being read repeatedly leading to more read capacity unit consumption, you can use DAX to offload your DynamoDB and lower your overall cost.
- Updating and managing leaderboards in gaming applications.
- Caching your data to provide faster response time in microseconds.
- Instant messaging applications
- Storing session data
- Real-time analytics
- Rich media streaming applications etc.
Overall Difference between Amazon DynamoDB Accelerator (DAX) and ElastiCache
We are pretty much clear on both of these caching offering now. Let’s summarize on how they are different.
|Amazon DynamoDB Accelerator(DAX)||Amazon ElastiCache|
|Works with only DynamoDB||Works with various applications and databases on AWS and on prem.|
|No caching logic required in application. DAX handles all.||Caching needs to be handled on application side.|
|LIttle to no code change required. Just change to use DAX client and you are good to go.||Heavy code change required to leverage cache.|
|Custom cache for DynamoDB||ElastiCache supports two open-source in-memory caching engines: Memcached and Redis|
|DAX manges cache invalidation||You manage cache invalidation|
|DAX gives you eventual consistency only.||Use ElastiCache or another caching service if you need strong consistency at microsecond response time|
Which One Should You Choose?
Just to give the finishing touch, DAX is specially designed to work with DynamoDB and supercharges your performance to next level.
If you are looking for a caching solution for your application that already uses DynamoDB without managing the caching on the application side and with minimum code changes and overhead, DAX is the way to go.
It’s like getting started with few clicks and client change. That’s it. It’s really easy and simple.
However, if you have an RDBMS or you wanna make a gaming leaderboard or to say simply if you have an existing application that leverages Redis or Memcached, go with ElastiCache. It is designed to simplify the setup, operation, and scaling of Memcached and Redis deployments on AWS.
Most of the time when caching is needed, you’ll want to go with DAX if you’re using DyanmoDB as a data store. Otherwise, use ElastiCache. Unless you have the need for strong consistency as discussed earlier.
In this post, we got to know about Amazon DynamoDB Accelerator DAX and Amazon ElastiCache. Additionally, we did a comparison of Amazon DynamoDB Accelerator DAX and Amazon ElastiCache.
We learnt that Amazon DynamoDB and DAX are a match made in heaven 🙂 . Going with an RDBMS , worry not – ElastiCache is always there for you.
After going through the detail, I hope you got a basic idea about both of these services. In case you have any doubts, feel free to drop in a comment.
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