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  1. Stackups
  2. Application & Data
  3. Container Registry
  4. Docker Registry
  5. Cloudflow vs Harbor

Cloudflow vs Harbor

OverviewComparisonAlternatives

Overview

Harbor
Harbor
Stacks183
Followers185
Votes11
GitHub Stars26.8K
Forks5.0K
Cloudflow
Cloudflow
Stacks5
Followers13
Votes0
GitHub Stars323
Forks89

Harbor vs Cloudflow: What are the differences?

Harbor: Manage and serve container images in a secure environment (created at VMware). Harbor is an open source cloud native registry that stores, signs, and scans container images for vulnerabilities Harbor solves common challenges by delivering trust, compliance, performance, and interoperability. It fills a gap for organ; Cloudflow: *Streaming Data Pipeline on Kubernetes *. It enables you to quickly develop, orchestrate, and operate distributed streaming applications on Kubernetes. With Cloudflow, streaming applications are comprised of small composable components wired together with schema-based contracts. It can dramatically accelerate streaming application development—​reducing the time required to create, package, and deploy—​from weeks to hours.

Harbor belongs to "Docker Registry" category of the tech stack, while Cloudflow can be primarily classified under "Big Data Tools".

Some of the features offered by Harbor are:

  • Multi-tenant content signing and validation
  • Image replication between instances
  • Extensible API and graphical UI

On the other hand, Cloudflow provides the following key features:

  • Apache Spark, Apache Flink, and Akka Streams
  • Focus only on business logic, leave the boilerplate to us
  • We provide all the tooling for going from business logic to a deployable Docker image

Harbor and Cloudflow are both open source tools. Harbor with 11.5K GitHub stars and 3.13K forks on GitHub appears to be more popular than Cloudflow with 172 GitHub stars and 50 GitHub forks.

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Detailed Comparison

Harbor
Harbor
Cloudflow
Cloudflow

Harbor is an open source cloud native registry that stores, signs, and scans container images for vulnerabilities. Harbor solves common challenges by delivering trust, compliance, performance, and interoperability. It fills a gap for organ

It enables you to quickly develop, orchestrate, and operate distributed streaming applications on Kubernetes. With Cloudflow, streaming applications are comprised of small composable components wired together with schema-based contracts. It can dramatically accelerate streaming application development—​reducing the time required to create, package, and deploy—​from weeks to hours.

Multi-tenant content signing and validation;Image replication between instances;Extensible API and graphical UI;Security and vulnerability analysis;Identity integration and role-based access control;Internationalization
Apache Spark, Apache Flink, and Akka Streams; Focus only on business logic, leave the boilerplate to us; We provide all the tooling for going from business logic to a deployable Docker image; We provide Kubernetes tooling to deploy your distributed system with a single command, and manage durable connections between processing stages; With a Lightbend subscription, you get all the tools you need to provide insights, observability, and lifecycle management for evolving your distributed streaming application
Statistics
GitHub Stars
26.8K
GitHub Stars
323
GitHub Forks
5.0K
GitHub Forks
89
Stacks
183
Stacks
5
Followers
185
Followers
13
Votes
11
Votes
0
Pros & Cons
Pros
  • 4
    Good on-premises container registry
  • 1
    Support multiple authentication methods
  • 1
    Supports OIDC
  • 1
    Supports LDAP/Active Directory
  • 1
    Perfect for Teams and Organizations
No community feedback yet
Integrations
Docker
Docker
Kubernetes
Kubernetes
Helm
Helm
Kubernetes
Kubernetes
Apache Spark
Apache Spark
Akka
Akka
Apache Flink
Apache Flink

What are some alternatives to Harbor, Cloudflow?

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.

Apache Spark

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Presto

Presto

Distributed SQL Query Engine for Big Data

Amazon Athena

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

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.

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