Alternatives to Azure Machine Learning logo

Alternatives to Azure Machine Learning

Python, Azure Databricks, Amazon SageMaker, Amazon Machine Learning, and Databricks are the most popular alternatives and competitors to Azure Machine Learning.
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What is Azure Machine Learning and what are its top alternatives?

Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.
Azure Machine Learning is a tool in the Machine Learning as a Service category of a tech stack.

Azure Machine Learning alternatives & related posts

Python logo

Python

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A clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
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Python
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Azure Machine Learning

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Nick Parsons
Nick Parsons
Director of Developer Marketing at Stream · | 34 upvotes · 435K views
atStreamStream
Stream
Stream
Go
Go
JavaScript
JavaScript
ES6
ES6
Node.js
Node.js
Babel
Babel
Yarn
Yarn
Python
Python
#FrameworksFullStack
#Languages

Winds 2.0 is an open source Podcast/RSS reader developed by Stream with a core goal to enable a wide range of developers to contribute.

We chose JavaScript because nearly every developer knows or can, at the very least, read JavaScript. With ES6 and Node.js v10.x.x, it’s become a very capable language. Async/Await is powerful and easy to use (Async/Await vs Promises). Babel allows us to experiment with next-generation JavaScript (features that are not in the official JavaScript spec yet). Yarn allows us to consistently install packages quickly (and is filled with tons of new tricks)

We’re using JavaScript for everything – both front and backend. Most of our team is experienced with Go and Python, so Node was not an obvious choice for this app.

Sure... there will be haters who refuse to acknowledge that there is anything remotely positive about JavaScript (there are even rants on Hacker News about Node.js); however, without writing completely in JavaScript, we would not have seen the results we did.

#FrameworksFullStack #Languages

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Jeyabalaji Subramanian
Jeyabalaji Subramanian
CTO at FundsCorner · | 24 upvotes · 591.1K views
atFundsCornerFundsCorner
MongoDB
MongoDB
PostgreSQL
PostgreSQL
MongoDB Stitch
MongoDB Stitch
Node.js
Node.js
Amazon SQS
Amazon SQS
Python
Python
SQLAlchemy
SQLAlchemy
AWS Lambda
AWS Lambda
Zappa
Zappa

Recently we were looking at a few robust and cost-effective ways of replicating the data that resides in our production MongoDB to a PostgreSQL database for data warehousing and business intelligence.

We set ourselves the following criteria for the optimal tool that would do this job: - The data replication must be near real-time, yet it should NOT impact the production database - The data replication must be horizontally scalable (based on the load), asynchronous & crash-resilient

Based on the above criteria, we selected the following tools to perform the end to end data replication:

We chose MongoDB Stitch for picking up the changes in the source database. It is the serverless platform from MongoDB. One of the services offered by MongoDB Stitch is Stitch Triggers. Using stitch triggers, you can execute a serverless function (in Node.js) in real time in response to changes in the database. When there are a lot of database changes, Stitch automatically "feeds forward" these changes through an asynchronous queue.

We chose Amazon SQS as the pipe / message backbone for communicating the changes from MongoDB to our own replication service. Interestingly enough, MongoDB stitch offers integration with AWS services.

In the Node.js function, we wrote minimal functionality to communicate the database changes (insert / update / delete / replace) to Amazon SQS.

Next we wrote a minimal micro-service in Python to listen to the message events on SQS, pickup the data payload & mirror the DB changes on to the target Data warehouse. We implemented source data to target data translation by modelling target table structures through SQLAlchemy . We deployed this micro-service as AWS Lambda with Zappa. With Zappa, deploying your services as event-driven & horizontally scalable Lambda service is dumb-easy.

In the end, we got to implement a highly scalable near realtime Change Data Replication service that "works" and deployed to production in a matter of few days!

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Azure Databricks logo

Azure Databricks

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Fast, easy, and collaborative Apache Spark–based analytics service
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    Azure Databricks
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    Azure Machine Learning
    Amazon SageMaker logo

    Amazon SageMaker

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    Accelerated Machine Learning
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      Amazon SageMaker
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      Azure Machine Learning

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      Julien DeFrance
      Julien DeFrance
      Principal Software Engineer at Tophatter · | 2 upvotes · 21.7K views
      atSmartZipSmartZip
      Serverless
      Serverless
      AWS Lambda
      AWS Lambda
      Amazon Machine Learning
      Amazon Machine Learning
      Amazon SageMaker
      Amazon SageMaker
      #PaaS
      #GCP
      #FaaS

      Which #IaaS / #PaaS to chose? Not all #Cloud providers are created equal. As you start to use one or the other, you'll build around very specific services that don't have their equivalent elsewhere.

      Back in 2014/2015, this decision I made for SmartZip was a no-brainer and #AWS won. AWS has been a leader, and over the years demonstrated their capacity to innovate, and reducing toil. Like no other.

      Year after year, this kept on being confirmed, as they rolled out new (managed) services, got into Serverless with AWS Lambda / FaaS And allowed domains such as #AI / #MachineLearning to be put into the hands of every developers thanks to Amazon Machine Learning or Amazon SageMaker for instance.

      Should you compare with #GCP for instance, it's not quite there yet. Building around these managed services, #AWS allowed me to get my developers on a whole new level. Where they know what's under the hood. Where they know they have these services available and can build around them. Where they care and are responsible for operations and security and deployment of what they've worked on.

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      Amazon Machine Learning logo

      Amazon Machine Learning

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      Visualization tools and wizards that guide you through the process of creating ML models w/o having to learn...
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        Amazon Machine Learning logo
        Amazon Machine Learning
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        Azure Machine Learning logo
        Azure Machine Learning

        related Amazon Machine Learning posts

        Julien DeFrance
        Julien DeFrance
        Principal Software Engineer at Tophatter · | 2 upvotes · 21.7K views
        atSmartZipSmartZip
        Serverless
        Serverless
        AWS Lambda
        AWS Lambda
        Amazon Machine Learning
        Amazon Machine Learning
        Amazon SageMaker
        Amazon SageMaker
        #PaaS
        #GCP
        #FaaS

        Which #IaaS / #PaaS to chose? Not all #Cloud providers are created equal. As you start to use one or the other, you'll build around very specific services that don't have their equivalent elsewhere.

        Back in 2014/2015, this decision I made for SmartZip was a no-brainer and #AWS won. AWS has been a leader, and over the years demonstrated their capacity to innovate, and reducing toil. Like no other.

        Year after year, this kept on being confirmed, as they rolled out new (managed) services, got into Serverless with AWS Lambda / FaaS And allowed domains such as #AI / #MachineLearning to be put into the hands of every developers thanks to Amazon Machine Learning or Amazon SageMaker for instance.

        Should you compare with #GCP for instance, it's not quite there yet. Building around these managed services, #AWS allowed me to get my developers on a whole new level. Where they know what's under the hood. Where they know they have these services available and can build around them. Where they care and are responsible for operations and security and deployment of what they've worked on.

        See more
        Databricks logo

        Databricks

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        A unified analytics platform, powered by Apache Spark
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          Databricks
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          Azure Machine Learning
          Amazon Elastic Inference logo

          Amazon Elastic Inference

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          GPU-Powered Deep Learning Inference Acceleration
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            Amazon Elastic Inference
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            Azure Machine Learning
            Algorithms.io logo

            Algorithms.io

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            Machine learning as a service for streaming data from connected devices.
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              Algorithms.io
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              Azure Machine Learning
              NanoNets logo

              NanoNets

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              Machine learning API with less data
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              NanoNets
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              Azure Machine Learning
              FloydHub logo

              FloydHub

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              Heroku for Deep Learning
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                FloydHub
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                Azure Machine Learning
                BigML logo

                BigML

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                Machine Learning, made simple. Predictive analytics for big data and not-so-big data.
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                BigML
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                Azure Machine Learning
                Firebase Predictions logo

                Firebase Predictions

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                Define dynamic user groups based on predicted behavior
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                  Firebase Predictions
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                  Azure Machine Learning
                  Amazon Personalize logo

                  Amazon Personalize

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                  Real-time personalization and recommendation
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                    Amazon Personalize
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                    Azure Machine Learning
                    Google AI Platform logo

                    Google AI Platform

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                    Create your AI applications once, then run them easily on both GCP and on-premises
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                      Google AI Platform
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                      Azure Machine Learning
                      Gradient° logo

                      Gradient°

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                      Deep learning platform built for developers
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                        Gradient°
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                        Azure Machine Learning
                        Lateral logo

                        Lateral

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                        The ultimate API for recommending your content
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                          Lateral
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                          Azure Machine Learning
                          GraphLab Create logo

                          GraphLab Create

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                          Machine learning platform that enables data scientists and app developers to easily create intelligent apps at scale
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                          GraphLab Create
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                          Azure Machine Learning
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                          Paperspace

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                          The way to access and manage limitless computing power in the cloud
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                            Azure Machine Learning
                            Lamina logo

                            Lamina

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                            Artificial Intelligence as an API 🤖
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                              Lamina
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                              Azure Machine Learning
                              wise.io logo

                              wise.io

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                              Machine Learning as a Service and Big Data Analytics
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                                Azure Machine Learning