Overview

Conductor

Stacks66

Followers122

Votes0

GitHub Stars12.8K

Forks2.3K

Nameko

Stacks20

Followers79

Votes0

GitHub Stars4.8K

Forks468

Conductor vs Nameko: What are the differences?

Introduction

When looking at Conductor and Nameko, it is important to understand their key differences in order to make an informed decision on which technology to use for your project.

Architecture: Conductor is a workflow orchestration engine that focuses on coordinating microservices whereas Nameko is a microservices framework that provides an easy way to create and deploy microservices. Conductor is more suitable for managing complex workflow processes across multiple microservices, while Nameko is better for building individual microservices.
Language Support: Conductor is written in Java and offers support for Java-based microservices, making it a good choice for organizations utilizing Java technologies. On the other hand, Nameko is written in Python and is well-suited for Python-based microservices, providing a seamless integration with Python codebases.
Community and Ecosystem: Conductor has a larger community and ecosystem around it, being developed and maintained by Netflix. This means that there are more resources, documentation, and support available for Conductor users. Nameko, although not as widely adopted as Conductor, is still actively maintained and has a dedicated community of users and contributors.
Feature Set: Conductor offers advanced features for workflow management such as DSL-based workflow definitions, support for conditional branching, parallel execution, and retries. Nameko, on the other hand, focuses on simplicity and ease of use, providing basic features for building and deploying microservices without the need for complex workflow management capabilities.
Scalability: Conductor is designed to handle large-scale workflows and can scale horizontally to meet high demands. Nameko, while capable of scaling, may not be as optimized for handling complex workflow orchestration at a large scale as Conductor.
Integration: Conductor integrates well with other Netflix open-source projects such as Zuul, Eureka, and Ribbon, making it a good choice for organizations already using Netflix technologies. Nameko, on the other hand, can easily integrate with various Python libraries and frameworks, providing flexibility for developers working in Python environments.

In Summary, Conductor and Nameko differ in architecture focus, language support, community support, feature set, scalability, and integration capabilities.

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Advice on Conductor, Nameko

Girish

Software Engineer at FireVisor Systems

Apr 17, 2020

Needs adviceon

Python

Nameko

RabbitMQ

Which is the best Python framework for microservices?

We are using Nameko for building microservices in Python. The things we really like are dependency injection and the ease with which one can expose endpoints via RPC over RabbitMQ. We are planning to try a tool that helps us write polyglot microservices and nameko is not super compatible with it. Also, we are a bit worried about the not so good community support from nameko and looking for a python alternate to write microservices.

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Comments

Detailed Comparison

Conductor	Nameko
Conductor is an orchestration engine that runs in the cloud.	Python microservices framework that leverages AMQP for RPC. It supports asynchronous and synchronous events.
Allow creating complex process / business flows in which individual task is implemented by a microservice.;A JSON DSL based blueprint defines the execution flow.;Provide visibility and traceability into the these process flows.;Expose control semantics around pause, resume, restart, etc allowing for better devops experience.;Allow greater reuse of existing microservices providing an easier path for onboarding.;User interface to visualize the process flows.;Ability to synchronously process all the tasks when needed.;Ability to scale millions of concurrently running process flows.;Backed by a queuing service abstracted from the clients.;Be able to operate on HTTP or other transports e.g. gRPC.	Focus on business logic; Distributed and scalable; Extensible
Statistics
GitHub Stars 12.8K	GitHub Stars 4.8K
GitHub Forks 2.3K	GitHub Forks 468
Stacks 66	Stacks 20
Followers 122	Followers 79
Votes 0	Votes 0
Integrations
No integrations available	Django Slack Python Redis Sentry SQLAlchemy

What are some alternatives to Conductor, Nameko?

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Sinatra

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Lumen

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Fastify

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hapi

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TypeORM

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