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AWS Lambda vs PostgREST: What are the differences?
Introduction: In comparing AWS Lambda and PostgREST, it is essential to highlight their key differences to determine which platform suits specific application requirements.
- Deployment Model: AWS Lambda operates on a serverless architecture, where the user only pays for the actual compute time used, while PostgREST is designed to be deployed on traditional servers or cloud infrastructure, requiring more management and maintenance overhead.
- Use Case: AWS Lambda is primarily used for running serverless functions and event-driven tasks, providing scalability and cost-effectiveness for small to medium applications, whereas PostgREST is ideal for creating RESTful APIs on top of PostgreSQL databases, catering to data-centric applications.
- Programming Language Support: AWS Lambda supports multiple programming languages such as Node.js, Python, and Java, allowing developers to choose their preferred language, while PostgREST is specifically designed to work with PostgreSQL, limiting language flexibility to SQL queries and functions.
- Scalability: AWS Lambda can scale automatically based on incoming traffic and workload, ensuring high availability and performance, while PostgREST scalability relies on the underlying infrastructure and database configurations, which may require additional optimization.
- Cost Structure: AWS Lambda follows a pay-as-you-go pricing model, enabling cost efficiency for sporadic workloads, whereas PostgREST may involve fixed infrastructure costs and database usage fees, making it less suitable for unpredictable or fluctuating workloads.
- Maintenance and Monitoring: AWS Lambda includes built-in monitoring and logging tools for tracking function performance and errors, simplifying maintenance tasks, while PostgREST users are responsible for implementing monitoring and logging solutions independently to ensure system health and reliability.
In Summary, the key differences between AWS Lambda and PostgREST lie in their deployment model, use case, programming language support, scalability, cost structure, and maintenance requirements, each catering to distinct application needs and preferences.
Need advice on what platform, systems and tools to use.
Evaluating whether to start a new digital business for which we will need to build a website that handles all traffic. Website only right now. May add smartphone apps later. No desktop app will ever be added. Website to serve various countries and languages. B2B and B2C type customers. Need to handle heavy traffic, be low cost, and scale well.
We are open to either build it on AWS or on Microsoft Azure.
Apologies if I'm leaving out some info. My first post. :) Thanks in advance!
I recommend this : -Spring reactive for back end : the fact it's reactive (async) it consumes half of the resources that a sync platform needs (so less CPU -> less money). -Angular : Web Front end ; it's gives you the possibility to use PWA which is a cheap replacement for a mobile app (but more less popular). -Docker images. -Kubernetes to orchestrate all the containers. -I Use Jenkins / blueocean, ansible for my CI/CD (with Github of course) -AWS of course : u can run a K8S cluster there, make it multi AZ (availability zones) to be highly available, use a load balancer and an auto scaler and ur good to go. -You can store data by taking any managed DB or u can deploy ur own (cheap but risky).
You pay less money, but u need some technical 2 - 3 guys to make that done.
Good luck
My advice will be Front end: React Backend: Language: Java, Kotlin. Database: SQL: Postgres, MySQL, Aurora NOSQL: Mongo db. Caching: Redis. Public : Spring Webflux for async public facing operation. Admin api: Spring boot, Hibrernate, Rest API. Build Container image. Kuberenetes: AWS EKS, AWS ECS, Google GKE. Use Jenkins for CI/CD pipeline. Buddy works is good for AWS. Static content: Host on AWS S3 bucket, Use Cloudfront or Cloudflare as CDN.
Serverless Solution: Api gateway Lambda, Serveless Aurora (SQL). AWS S3 bucket.
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 PostgREST
- Fast, simple, powerful REST APIs from vanilla Postgres4
- JWT authentication2
- Very fast1
- Declarative role based security at the data layer1
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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 PostgREST
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What is AWS Lambda?
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