Software Alternatives, Accelerators & Startups

Azure Machine Learning Studio VS VeloDB

Compare Azure Machine Learning Studio VS VeloDB and see what are their differences

Azure Machine Learning Studio logo Azure Machine Learning Studio

Azure Machine Learning Studio is a GUI-based integrated development environment for constructing and operationalizing Machine Learning workflow on Azure.

VeloDB logo VeloDB

Modern Real-Time Data Warehouse
  • Azure Machine Learning Studio Landing page
    Landing page //
    2021-08-03
  • VeloDB VeloDB
    VeloDB //
    2024-01-10

VeloDB is a modern real-time data warehouse powered by open source Apache Doris for lightning-fast data analytics at scale. It ensures big data ingestion within seconds and outstanding performance in both real-time serving and interactive ad-hoc queries. It is one platform for various analytics workloads, including structured and semi-structured data processing, real-time analytics and batch processing, internal data query and federated queries of external data. It allows elastic scaling for efficient resource management. It can dynamically adjust the computing resources allocated to the workload based on the changing requirements. It supports MySQL protocol and standard SQL for easy integration with other data tools. It also provides open data API to be accessible for various external query engines.

Azure Machine Learning Studio videos

Azure Machine Learning Studio

More videos:

  • Review - Introduction to Microsoft Azure Machine Learning Studio & Services

VeloDB videos

No VeloDB videos yet. You could help us improve this page by suggesting one.

+ Add video

Category Popularity

0-100% (relative to Azure Machine Learning Studio and VeloDB)
Data Science And Machine Learning
Data Warehousing
0 0%
100% 100
Machine Learning
100 100%
0% 0
Databases
0 0%
100% 100

User comments

Share your experience with using Azure Machine Learning Studio and VeloDB. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, Azure Machine Learning Studio seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Azure Machine Learning Studio mentions (2)

  • What are all possible FREE Machine Learning integrations with Power BI?
    Machine Learning studio https://studio.azureml.net/ but this will be discontinued in Dec 01,2021 :(. Source: over 2 years ago
  • Stumbling into BI as a job role and need advice
    Advanced analytics, predictive modeling: You can't go passed learning R or Python if you're that way inclined.. however, if you're a GUI monkey like me, I have had a fair amount of success using https://studio.azureml.net/ it's free at base level :). Source: almost 3 years ago

VeloDB mentions (0)

We have not tracked any mentions of VeloDB yet. Tracking of VeloDB recommendations started around Jan 2024.

What are some alternatives?

When comparing Azure Machine Learning Studio and VeloDB, you can also consider the following products

IBM Watson Studio - Learn more about Watson Studio. Increase productivity by giving your team a single environment to work with the best of open source and IBM software, to build and deploy an AI solution.

Snowflakepowe.red - Snowflake Computing is delivering a data warehouse for the cloud.

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.

Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.

Presto - Next generation front-of-house technology