![]() ![]() Here are several benefits of using a cache in front of MongoDB: Regardless of the model you choose, adding a serverless cache like Momento can dramatically improve performance, provide a better user experience, and even help to reduce costs. There are many flavors of MongoDB now, including the traditional self-hosted model, as well as MongoDB Atlas in serverless, dedicated, and shared modes. Not only that, but spiky workloads (a place where serverless really shines) can easily overwhelm a MongoDB cluster that’s underprovisioned. Like any database, MongoDB has its limitations, especially once traffic increases. In this post, let’s take a look at some of the benefits of adding a serverless cache like Momento in front of your MongoDB cluster, as well as some real world examples where caching can supercharge your serverless application backed by MongoDB. Serverless had been missing a great caching solution, but now with Momento in hand, we can do some pretty amazing things without adding all that extra overhead. You only pay for what you use and it instantly scales to meet your workloads. Then late last year, I discovered Momento, a serverless cache that was truly serverless. Traditionally, the problem with caching in serverless applications, at least in the AWS ecosystem, is that you had to both run your Lambda functions in a VPC (which limits access to the Internet without a Managed NAT Gateway) and you had to provision an ElastiCache cluster and manage it yourself. I’ve been impressed so far, and I look forward to even more progress.Įven though MongoDB is widely appreciated for its flexibility and versatility, like any database system, when you scale up and usage increases, performance will likely take a hit. About a year ago, MongoDB made a serverless version of their MongoDB Atlas service generally available, which prompted me to take another look. I have a lot of experience with Amazon DynamoDB and Cassandra, both excellent solutions for the right use cases, but I’ve always loved MongoDB and the flexibility of its query language. I’ve seen some very promising progress in this area, but for me, I’m still a big fan of using NoSQL solutions with my serverless applications.ĭon’t get me wrong, I love the capabilities of MySQL and Postgres, but NoSQL databases have a combination of flexibility, scalability, and connection methods that highly complement a serverless approach. Recently there have been numerous investments in “serverless databases” to bring familiar RDBMS offerings to the growing number of serverless workloads. What used to be a great tool for a limited set of use cases has turned into an extremely powerful ecosystem filled with products, services, and frameworks that not only negate nearly every objection, but allows developers to build native cloud applications very quickly. A lot has changed in the 8 years since I started building serverless applications.
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