AWS Lambda vs peewee

Overview

peewee

Stacks50

Followers105

Votes19

GitHub Stars11.8K

Forks1.4K

AWS Lambda

Stacks26.0K

Followers18.8K

Votes432

AWS Lambda vs peewee: What are the differences?

Introduction

In this section, we will be discussing the key differences between AWS Lambda and peewee.

Scalability: AWS Lambda provides serverless compute capabilities where you can easily scale your code based on the demand. It automatically manages the resources for you, so you don't have to worry about provisioning or managing servers. On the other hand, peewee is an Object-Relational Mapping (ORM) library for Python that helps you interact with databases. It does not provide automatic scalability and requires you to manage the database servers yourself.
Event-driven architecture: AWS Lambda follows an event-driven architecture, where you can trigger your functions based on events from various sources like API Gateway, S3 buckets, or even custom events. This allows you to build serverless applications that react to changes in real-time. On the other hand, peewee is primarily focused on database operations and does not provide built-in event-driven capabilities.
Billing Model: AWS Lambda bills you based on the number of requests and the duration of your function execution. You only pay for the actual usage of your functions. In contrast, peewee is an open-source library and does not have any direct billing. However, you still need to consider the costs associated with maintaining and managing the underlying infrastructure, such as database servers.
Language Support: AWS Lambda supports multiple programming languages, including Java, Python, Node.js, C#, and more. This allows you to choose the language that best suits your application's requirements. On the other hand, peewee is specifically designed for Python, and its core functionalities are optimized for Python-based projects.
Deployment Flexibility: AWS Lambda allows you to deploy your functions on the AWS Cloud, making it easily accessible from anywhere on the internet. It integrates well with other AWS services and provides seamless deployment capabilities through the AWS Management Console or the AWS Command Line Interface (CLI). On the other hand, peewee is a Python library that can be used in any Python project. It does not have any specific deployment requirements and can be used in various deployment scenarios.
Managed Service vs. Library: AWS Lambda is a fully managed service provided by Amazon Web Services (AWS). It takes care of infrastructure provisioning, deployment, scaling, and monitoring, allowing you to focus solely on writing the code. Peewee, on the other hand, is a Python library that you need to integrate into your application code. It provides you with the necessary tools and abstractions to interact with databases but does not provide the same level of managed services as AWS Lambda.

In summary, AWS Lambda offers serverless compute capabilities, event-driven architecture, automatic scalability, and managed services, making it suitable for building highly scalable and event-driven applications. On the other hand, peewee is an ORM library for Python, focused on database operations, without the built-in scalability and managed services provided by AWS Lambda.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Advice on peewee, AWS Lambda

Tim

CTO at Checkly Inc.

Sep 18, 2019

Needs adviceon

Heroku

AWS Lambda

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

357k views357k

Comments

Mark

Nov 2, 2020

Needs adviceon

Microsoft Azure

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!

133k views133k

Comments

Detailed Comparison

peewee	AWS Lambda
A small, expressive orm, written in python (2.6+, 3.2+), with built-in support for sqlite, mysql and postgresql and special extensions like hstore.	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.
-	Extend other AWS services with custom logic;Build custom back-end services;Completely Automated Administration;Built-in Fault Tolerance;Automatic Scaling;Integrated Security Model;Bring Your Own Code;Pay Per Use;Flexible Resource Model
Statistics
GitHub Stars 11.8K	GitHub Stars -
GitHub Forks 1.4K	GitHub Forks -
Stacks 50	Stacks 26.0K
Followers 105	Followers 18.8K
Votes 19	Votes 432
Pros & Cons
Pros 7 Easy to start 4 Open Source 4 Free 4 High Performance	Pros 129 No infrastructure 83 Cheap 70 Quick 59 Stateless 47 No deploy, no server, great sleep Cons 7 Cant execute ruby or go 3 Compute time limited 1 Can't execute PHP w/o significant effort
Integrations
PostgreSQL MySQL SQLite	No integrations available

What are some alternatives to peewee, AWS Lambda?

Sequelize

Sequelize is a promise-based ORM for Node.js and io.js. It supports the dialects PostgreSQL, MySQL, MariaDB, SQLite and MSSQL and features solid transaction support, relations, read replication 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.

Google Cloud Run

A managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It's serverless by abstracting away all infrastructure management.

Prisma

Prisma is an open-source database toolkit. It replaces traditional ORMs and makes database access easy with an auto-generated query builder for TypeScript & Node.js.

Hibernate

Hibernate is a suite of open source projects around domain models. The flagship project is Hibernate ORM, the Object Relational Mapper.

Doctrine 2

Doctrine 2 sits on top of a powerful database abstraction layer (DBAL). One of its key features is the option to write database queries in a proprietary object oriented SQL dialect called Doctrine Query Language (DQL), inspired by Hibernates HQL.

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.

Google Cloud Functions

Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running

MikroORM

TypeScript ORM for Node.js based on Data Mapper, Unit of Work and Identity Map patterns. Supports MongoDB, MySQL, MariaDB, PostgreSQL and SQLite databases.

Knative

Knative provides a set of middleware components that are essential to build modern, source-centric, and container-based applications that can run anywhere: on premises, in the cloud, or even in a third-party data center

Related Comparisons

AWS Lambda vs peewee: What are the differences?

Introduction

In this section, we will be discussing the key differences between AWS Lambda and peewee.

Scalability: AWS Lambda provides serverless compute capabilities where you can easily scale your code based on the demand. It automatically manages the resources for you, so you don't have to worry about provisioning or managing servers. On the other hand, peewee is an Object-Relational Mapping (ORM) library for Python that helps you interact with databases. It does not provide automatic scalability and requires you to manage the database servers yourself.
Event-driven architecture: AWS Lambda follows an event-driven architecture, where you can trigger your functions based on events from various sources like API Gateway, S3 buckets, or even custom events. This allows you to build serverless applications that react to changes in real-time. On the other hand, peewee is primarily focused on database operations and does not provide built-in event-driven capabilities.
Billing Model: AWS Lambda bills you based on the number of requests and the duration of your function execution. You only pay for the actual usage of your functions. In contrast, peewee is an open-source library and does not have any direct billing. However, you still need to consider the costs associated with maintaining and managing the underlying infrastructure, such as database servers.
Language Support: AWS Lambda supports multiple programming languages, including Java, Python, Node.js, C#, and more. This allows you to choose the language that best suits your application's requirements. On the other hand, peewee is specifically designed for Python, and its core functionalities are optimized for Python-based projects.
Deployment Flexibility: AWS Lambda allows you to deploy your functions on the AWS Cloud, making it easily accessible from anywhere on the internet. It integrates well with other AWS services and provides seamless deployment capabilities through the AWS Management Console or the AWS Command Line Interface (CLI). On the other hand, peewee is a Python library that can be used in any Python project. It does not have any specific deployment requirements and can be used in various deployment scenarios.
Managed Service vs. Library: AWS Lambda is a fully managed service provided by Amazon Web Services (AWS). It takes care of infrastructure provisioning, deployment, scaling, and monitoring, allowing you to focus solely on writing the code. Peewee, on the other hand, is a Python library that you need to integrate into your application code. It provides you with the necessary tools and abstractions to interact with databases but does not provide the same level of managed services as AWS Lambda.

AWS Lambda vs peewee

Overview

AWS Lambda vs peewee: What are the differences?