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AWS Lambda vs MongoDB Stitch: What are the differences?

Introduction: In the world of cloud computing, AWS Lambda and MongoDB Stitch are two popular serverless computing solutions that offer different capabilities and features. Below are the key differences between AWS Lambda and MongoDB Stitch.

  1. Programming Languages Supported: AWS Lambda supports a variety of programming languages such as Node.js, Python, Java, and C#. In contrast, MongoDB Stitch primarily supports JavaScript and TypeScript for creating serverless functions. This difference in language support can influence the development team's choice based on their familiarity and expertise with a particular language.

  2. Database Integration: MongoDB Stitch is specifically designed to integrate seamlessly with MongoDB databases, allowing developers to easily access and manipulate data stored in MongoDB collections. On the other hand, AWS Lambda provides more flexibility in terms of database integration, allowing developers to connect to various databases like Amazon DynamoDB, Amazon RDS, and others. The choice between AWS Lambda and MongoDB Stitch may depend on the preferred database system and the complexity of data operations required.

  3. Pricing Model: AWS Lambda follows a pay-as-you-go pricing model, where users are charged based on the number of requests and the duration of code execution. MongoDB Stitch offers a free tier with limited resources and charges based on the number of invocations and data transfer. Depending on the scale and usage patterns of the application, developers can choose the pricing model that aligns with their budget and requirements.

  4. Vendor Lock-in: AWS Lambda is a service provided by Amazon Web Services (AWS), which may lead to potential vendor lock-in for organizations heavily invested in the AWS ecosystem. MongoDB Stitch, on the other hand, provides more flexibility in terms of deployment options, as it can be integrated with various cloud platforms and on-premises environments, reducing the risk of vendor lock-in. This difference can be a crucial factor for organizations looking to maintain portability and avoid dependency on a single cloud provider.

  5. Event Triggers: AWS Lambda offers a wide range of event sources for triggering serverless functions, including API Gateway, S3, DynamoDB, and more. In comparison, MongoDB Stitch has more limited event trigger options, mainly focusing on database changes within MongoDB collections. Depending on the application's requirements and the need for diverse event sources, developers can choose between AWS Lambda and MongoDB Stitch for event-driven architecture implementations.

Summary: In summary, AWS Lambda and MongoDB Stitch differ in terms of programming language support, database integration, pricing model, vendor lock-in considerations, and event trigger options, providing developers with a range of factors to consider when choosing a serverless computing solution.

Decisions about AWS Lambda and MongoDB Stitch

When adding a new feature to Checkly rearchitecting some older piece, I tend to pick Heroku for rolling it out. But not always, because sometimes I pick AWS Lambda . The short story:

  • Developer Experience trumps everything.
  • AWS Lambda is cheap. Up to a limit though. This impact not only your wallet.
  • If you need geographic spread, AWS is lonely at the top.
The setup

Recently, I was doing a brainstorm at a startup here in Berlin on the future of their infrastructure. They were ready to move on from their initial, almost 100% Ec2 + Chef based setup. Everything was on the table. But we crossed out a lot quite quickly:

  • Pure, uncut, self hosted Kubernetes — way too much complexity
  • Managed Kubernetes in various flavors — still too much complexity
  • Zeit — Maybe, but no Docker support
  • Elastic Beanstalk — Maybe, bit old but does the job
  • Heroku
  • Lambda

It became clear a mix of PaaS and FaaS was the way to go. What a surprise! That is exactly what I use for Checkly! But when do you pick which model?

I chopped that question up into the following categories:

  • Developer Experience / DX 🤓
  • Ops Experience / OX 🐂 (?)
  • Cost 💵
  • Lock in 🔐

Read the full post linked below for all details

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Pros of AWS Lambda
Pros of MongoDB Stitch
  • 129
    No infrastructure
  • 83
    Cheap
  • 70
    Quick
  • 59
    Stateless
  • 47
    No deploy, no server, great sleep
  • 12
    AWS Lambda went down taking many sites with it
  • 6
    Event Driven Governance
  • 6
    Extensive API
  • 6
    Auto scale and cost effective
  • 6
    Easy to deploy
  • 5
    VPC Support
  • 3
    Integrated with various AWS services
  • 2
    Static Hosting
  • 1
    Serverless
  • 1
    Best integration with MongoDB (Atlas)

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Cons of AWS Lambda
Cons of MongoDB Stitch
  • 7
    Cant execute ruby or go
  • 3
    Compute time limited
  • 1
    Can't execute PHP w/o significant effort
    Be the first to leave a con

    Sign up to add or upvote consMake informed product decisions

    What is AWS Lambda?

    AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.

    What is MongoDB Stitch?

    MongoDB Stitch lets developers focus on building applications rather than on managing data manipulation code, service integration, or backend infrastructure. Stitch lets you focus on building the app users want, not on writing boilerplate backend logic.

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    What companies use AWS Lambda?
    What companies use MongoDB Stitch?
    See which teams inside your own company are using AWS Lambda or MongoDB Stitch.
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    What tools integrate with AWS Lambda?
    What tools integrate with MongoDB Stitch?

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    Blog Posts

    GitHubPythonNode.js+47
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    GitHubDockerAmazon EC2+23
    12
    6559
    JavaScriptGitHubPython+42
    53
    21795
    What are some alternatives to AWS Lambda and MongoDB Stitch?
    Serverless
    Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.
    Azure Functions
    Azure Functions is an event driven, compute-on-demand experience that extends the existing Azure application platform with capabilities to implement code triggered by events occurring in virtually any Azure or 3rd party service as well as on-premises systems.
    AWS Elastic Beanstalk
    Once you upload your application, Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring.
    AWS Step Functions
    AWS Step Functions makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Building applications from individual components that each perform a discrete function lets you scale and change applications quickly.
    Google App Engine
    Google has a reputation for highly reliable, high performance infrastructure. With App Engine you can take advantage of the 10 years of knowledge Google has in running massively scalable, performance driven systems. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow.
    See all alternatives