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Pros of Kubeflow
Pros of Pachyderm
  • 9
    System designer
  • 3
  • 3
    Kfp dsl
  • 2
    Google backed
  • 3
  • 1
  • 1
    Can run on GCP or AWS

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What is Kubeflow?

The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.

What is Pachyderm?

Pachyderm is an open source MapReduce engine that uses Docker containers for distributed computations.

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Jobs that mention Kubeflow and Pachyderm as a desired skillset
Philippines National Capital Region Makati City
United States of America Texas Richardson
United Kingdom of Great Britain and Northern Ireland England Feltham
India Telangana Hyderabad
India Telangana Hyderabad
What companies use Kubeflow?
What companies use Pachyderm?
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What tools integrate with Kubeflow?
What tools integrate with Pachyderm?

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What are some alternatives to Kubeflow and Pachyderm?
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
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.
MLflow is an open source platform for managing the end-to-end machine learning lifecycle.
Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
An enterprise-grade open source platform for building, training, and monitoring large scale deep learning applications.
See all alternatives