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AWS Lambda vs NSQ: What are the differences?
What is AWS Lambda? 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.
What is NSQ? A realtime distributed messaging platform. NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.
AWS Lambda can be classified as a tool in the "Serverless / Task Processing" category, while NSQ is grouped under "Message Queue".
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, NSQ provides the following key features:
- support distributed topologies with no SPOF
- horizontally scalable (no brokers, seamlessly add more nodes to the cluster)
- low-latency push based message delivery (performance)
"No infrastructure" is the primary reason why developers consider AWS Lambda over the competitors, whereas "It's in golang" was stated as the key factor in picking NSQ.
NSQ is an open source tool with 15.5K GitHub stars and 2.04K GitHub forks. Here's a link to NSQ's open source repository on GitHub.
According to the StackShare community, AWS Lambda has a broader approval, being mentioned in 1002 company stacks & 585 developers stacks; compared to NSQ, which is listed in 21 company stacks and 8 developer stacks.
I am looking into IoT World Solution where we have MQTT Broker. This MQTT Broker Sits in one of the Data Center. We are doing a lot of Alert and Alarm related processing on that Data, Currently, we are looking into Solution which can do distributed persistence of log/alert primarily on remote Disk.
Our primary need is to use lightweight where operational complexity and maintenance costs can be significantly reduced. We want to do it on-premise so we are not considering cloud solutions.
We looked into the following alternatives:
Apache Kafka - Great choice but operation and maintenance wise very complex. Rabbit MQ - High availability is the issue, Apache Pulsar - Operational Complexity. NATS - Absence of persistence. Akka Streams - Big learning curve and operational streams.
So we are looking into a lightweight library that can do distributed persistence preferably with publisher and subscriber model. Preferable on JVM stack.
Kafka is best fit here. Below are the advantages with Kafka ACLs (Security), Schema (protobuf), Scale, Consumer driven and No single point of failure.
Operational complexity is manageable with open source monitoring tools.
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 NSQ
- It's in golang29
- Distributed20
- Lightweight20
- Easy setup18
- High throughput17
- Publish-Subscribe11
- Scalable8
- Save data if no subscribers are found8
- Open source6
- Temporarily kept on disk5
- Simple-to use2
- Free1
- Topics and channels concept1
- Load balanced1
- Primarily in-memory1
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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 NSQ
- Long term persistence1
- Get NSQ behavior out of Kafka but not inverse1
- HA1
