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  5. Dapr vs Netflix OSS

Dapr vs Netflix OSS

OverviewComparisonAlternatives

Overview

Netflix OSS
Netflix OSS
Stacks76
Followers145
Votes0
Dapr
Dapr
Stacks96
Followers336
Votes9
GitHub Stars25.2K
Forks2.0K

Dapr vs Netflix OSS: What are the differences?

Introduction

Dapr is an open-source runtime that enables building microservices applications in a language-agnostic way. Netflix OSS (Open Source Software) is a suite of tools and frameworks developed by Netflix to support the company's microservices architecture. Although both Dapr and Netflix OSS focus on enabling the development of microservices, there are significant differences between the two.

  1. Architecture: Dapr is designed as a sidecar architecture, where Dapr instances run alongside each microservice. It allows each microservice to be developed independently without being tied to a specific framework or technology stack. In contrast, Netflix OSS integrates various functionalities within specific frameworks, such as Eureka for service discovery and Hystrix for fault tolerance.

  2. Language Support: Dapr supports a wide range of programming languages, including .NET, Java, Python, and Node.js, among others. This language-agnostic approach allows developers to choose the most suitable language for each microservice. Netflix OSS, on the other hand, primarily focuses on Java and provides libraries and frameworks specific to Java development.

  3. Community & Ecosystem: Dapr has a growing community of contributors and offers integrations with various cloud platforms, messaging systems, and observability tools. This vibrant ecosystem allows developers to easily leverage existing integrations to build and deploy microservices applications. Netflix OSS, although widely used within Netflix, has a more specialized ecosystem primarily focused on Java and lacks the same level of third-party integrations.

  4. Flexibility: Dapr provides a range of building blocks, called "Dapr components," that abstract away common microservices patterns, such as state management, pub/sub messaging, and service invocation. Developers can choose and configure these components according to their specific requirements. In contrast, Netflix OSS provides a more opinionated set of tools and frameworks, imposing a specific way of implementing microservices patterns.

  5. Cloud-Native & Kubernetes Focus: Dapr is built with a cloud-native and Kubernetes-first mindset, offering features like automatic sidecar injection in Kubernetes and built-in support for popular cloud platforms like Azure, AWS, and GCP. Netflix OSS, while compatible with Kubernetes, was initially designed for Netflix's own data centers and may not have the same level of integration and native support in cloud-native environments.

  6. Similarities: Despite the differences, both Dapr and Netflix OSS aim to simplify microservices development and provide tools for building scalable, resilient, and highly-available architectures. They both offer solutions for service discovery, load balancing, circuit-breaking, and observability, although with different approaches and implementations.

In summary, Dapr and Netflix OSS have significant differences in their architectural design, language support, ecosystem, flexibility, cloud-native focus, and level of integration. While Dapr offers a language-agnostic, sidecar-based, and extensible approach, Netflix OSS is more Java-centric, opinionated, and tailored for Netflix's own infrastructure.

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Detailed Comparison

Netflix OSS
Netflix OSS
Dapr
Dapr

It provides tools and services to get the most out of your (big) data. It also provides runtime containers, libraries and services that power microservices.

It is a portable, event-driven runtime that makes it easy for developers to build resilient, stateless and stateful microservices that run on the cloud and edge and embraces the diversity of languages and developer frameworks.

-
Event-driven Pub-Sub system with pluggable providers and at-least-once semantics; Input and Output bindings with pluggable providers; State management with pluggable data stores; Consistent service-to-service discovery and invocation; Opt-in stateful models: Strong/Eventual consistency, First-write/Last-write wins; Cross platform Virtual Actors; Rate limiting; Built-in distributed tracing using Open Telemetry; Runs natively on Kubernetes using a dedicated Operator and CRDs; Supports all programming languages via HTTP and gRPC; Multi-Cloud, open components (bindings, pub-sub, state) from Azure, AWS, GCP; Runs anywhere - as a process or containerized; Lightweight (58MB binary, 4MB physical memory); Runs as a sidecar - removes the need for special SDKs or libraries; Dedicated CLI - developer friendly experience with easy debugging; Clients for Java, Dotnet, Go, Javascript and Python
Statistics
GitHub Stars
-
GitHub Stars
25.2K
GitHub Forks
-
GitHub Forks
2.0K
Stacks
76
Stacks
96
Followers
145
Followers
336
Votes
0
Votes
9
Pros & Cons
No community feedback yet
Pros
  • 3
    Manage inter-service state
  • 2
    MTLS "for free"
  • 2
    Zipkin app tracing "for free"
  • 2
    App dashboard for rapid log overview
Cons
  • 1
    Additional overhead
Integrations
No integrations available
.NET Core
.NET Core
Java
Java
Python
Python
Microsoft Azure
Microsoft Azure
Kubernetes
Kubernetes
JavaScript
JavaScript
Google Cloud Platform
Google Cloud Platform
Golang
Golang

What are some alternatives to Netflix OSS, Dapr?

Kubernetes

Kubernetes

Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.

Rancher

Rancher

Rancher is an open source container management platform that includes full distributions of Kubernetes, Apache Mesos and Docker Swarm, and makes it simple to operate container clusters on any cloud or infrastructure platform.

Docker Compose

Docker Compose

With Compose, you define a multi-container application in a single file, then spin your application up in a single command which does everything that needs to be done to get it running.

Docker Swarm

Docker Swarm

Swarm serves the standard Docker API, so any tool which already communicates with a Docker daemon can use Swarm to transparently scale to multiple hosts: Dokku, Compose, Krane, Deis, DockerUI, Shipyard, Drone, Jenkins... and, of course, the Docker client itself.

Tutum

Tutum

Tutum lets developers easily manage and run lightweight, portable, self-sufficient containers from any application. AWS-like control, Heroku-like ease. The same container that a developer builds and tests on a laptop can run at scale in Tutum.

Portainer

Portainer

It is a universal container management tool. It works with Kubernetes, Docker, Docker Swarm and Azure ACI. It allows you to manage containers without needing to know platform-specific code.

Istio

Istio

Istio is an open platform for providing a uniform way to integrate microservices, manage traffic flow across microservices, enforce policies and aggregate telemetry data. Istio's control plane provides an abstraction layer over the underlying cluster management platform, such as Kubernetes, Mesos, etc.

Codefresh

Codefresh

Automate and parallelize testing. Codefresh allows teams to spin up on-demand compositions to run unit and integration tests as part of the continuous integration process. Jenkins integration allows more complex pipelines.

Azure Service Fabric

Azure Service Fabric

Azure Service Fabric is a distributed systems platform that makes it easy to package, deploy, and manage scalable and reliable microservices. Service Fabric addresses the significant challenges in developing and managing cloud apps.

CAST.AI

CAST.AI

It is an AI-driven cloud optimization platform for Kubernetes. Instantly cut your cloud bill, prevent downtime, and 10X the power of DevOps.

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