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AWS Lambda vs Azure Cosmos DB: What are the differences?
Developers describe AWS Lambda as "Automatically run code in response to modifications to objects in Amazon S3 buckets, messages in Kinesis streams, or updates in DynamoDB". 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. On the other hand, Azure Cosmos DB is detailed as "A fully-managed, globally distributed NoSQL database service". Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.
AWS Lambda can be classified as a tool in the "Serverless / Task Processing" category, while Azure Cosmos DB is grouped under "NoSQL Database as a Service".
Some of the features offered by AWS Lambda are:
- Extend other AWS services with custom logic
- Build custom back-end services
- Completely Automated Administration
On the other hand, Azure Cosmos DB provides the following key features:
- Fully managed with 99.99% Availability SLA
- Elastically and highly scalable (both throughput and storage)
- Predictable low latency: <10ms @ P99 reads and <15ms @ P99 fully-indexed writes
"No infrastructure" is the top reason why over 121 developers like AWS Lambda, while over 13 developers mention "Best-of-breed NoSQL features" as the leading cause for choosing Azure Cosmos DB.
According to the StackShare community, AWS Lambda has a broader approval, being mentioned in 1022 company stacks & 612 developers stacks; compared to Azure Cosmos DB, which is listed in 24 company stacks and 24 developer stacks.
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.
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
Pros of AWS Lambda
- No infrastructure129
- Cheap83
- Quick70
- Stateless59
- No deploy, no server, great sleep47
- AWS Lambda went down taking many sites with it12
- Event Driven Governance6
- Extensive API6
- Auto scale and cost effective6
- Easy to deploy6
- VPC Support5
- Integrated with various AWS services3
Pros of Azure Cosmos DB
- Best-of-breed NoSQL features28
- High scalability22
- Globally distributed15
- Automatic indexing over flexible json data model14
- Tunable consistency10
- Always on with 99.99% availability sla10
- Javascript language integrated transactions and queries7
- Predictable performance6
- High performance5
- Analytics Store5
- Rapid Development2
- No Sql2
- Auto Indexing2
- Ease of use2
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Cons of AWS Lambda
- Cant execute ruby or go7
- Compute time limited3
- Can't execute PHP w/o significant effort1
Cons of Azure Cosmos DB
- Pricing18
- Poor No SQL query support4
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