Software Alternatives, Accelerators & Startups
Register | Login

Google Cloud Machine Learning VS Draxlr

Compare Google Cloud Machine Learning VS Draxlr and see what are their differences

Limey
Limey: Connect smarter with QR codes, links, sites, and digital business cards in one place. featured
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Google Cloud Machine Learning logo Google Cloud Machine Learning

Google Cloud Machine Learning is a service that enables user to easily build machine learning models, that work on any type of data, of any size.

Draxlr logo Draxlr

Turn SQL Data into Decisions. Build professional dashboards and data visualizations without technical expertise. Easily embed analytics anywhere, receive automated alerts, and discover AI-powered insights all through a straightforward interface.
Visit Website
  • Google Cloud Machine Learning Landing page
    Landing page //
    2023-09-12
  • Draxlr Dashboard
    Dashboard //
    2025-01-17
  • Draxlr
    Image date //
    2025-01-17
  • Draxlr
    Image date //
    2025-01-17

Draxlr is a tool to analyze and monitor your data. It can help you get answers from your database, without writing code. These answers and insights can be shared with your team and customers. You can build graphs, charts, and dashboards and share them as links, images, or embed them on your website and app. Not only that you can set up monitoring on your data, so if any data changes you can be alerted via Slack and Email.

Google Cloud Machine Learning features and specs

  • Integrated Environment
    Vertex AI offers a unified API and user interface for all types of machine learning workloads, simplifying the development and deployment process.
  • Scalability
    It allows for easy scaling from individual experiments to large-scale production models, leveraging Google Cloud’s robust infrastructure.
  • Automated Machine Learning (AutoML)
    Vertex AI includes AutoML capabilities that enable users to build high-quality models with minimal intervention, making it accessible for users with varying expertise levels.
  • Integration with Google Services
    Seamless integration with other Google services, such as BigQuery, Dataflow, and Google Kubernetes Engine (GKE), enhances data processing and model deployment capabilities.
  • Cost Management
    Detailed cost management and budgeting tools help users monitor and control expenses effectively.
  • Pre-trained Models
    Access to Google's extensive library of pre-trained models can accelerate the development process and improve model performance.
  • Security
    Google Cloud's security protocols and compliance certifications ensure that data and models are safeguarded.

Possible disadvantages of Google Cloud Machine Learning

  • Complexity
    Even though Vertex AI aims to simplify machine learning operations, it may still be complex for beginners to fully leverage all its features.
  • Cost
    While providing robust tools, the expenses can add up, especially for large-scale operations or heavy usage of cloud resources.
  • Learning Curve
    There is a steep learning curve associated with mastering the various tools and services offered within the Vertex AI ecosystem.
  • Dependency on Google Ecosystem
    Heavy reliance on other Google Cloud services could become a hindrance if there's a need to migrate to a different cloud provider.
  • Limited Customization
    Pre-trained models and AutoML might limit the level of customization that advanced users require for highly specific use cases.

Draxlr features and specs

  • Dashboards and Visualizations
  • Slack Notifications
  • Email notifications
  • Query Builder
  • Embedded Analytics
  • Data Export

Google Cloud Machine Learning videos

No Google Cloud Machine Learning videos yet. You could help us improve this page by suggesting one.

Add video

Draxlr videos

+ Add

Get answers from your database data.

More videos:

  • Review - Draxlr lietime deal | Appsumo lifetime deal #bestsowftware
  • Review - Draxlr | Get more from your database for less with code-free data query tools #shorts

Category Popularity

0-100% (relative to Google Cloud Machine Learning and Draxlr)

Google Cloud Machine Learning

Draxlr

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Business Intelligence
0 0%
Business Intelligence
100% 100

User comments

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

Reviews

These are some of the external sources and on-site user reviews we've used to compare Google Cloud Machine Learning and Draxlr

Google Cloud Machine Learning Reviews

We have no reviews of Google Cloud Machine Learning yet.
Be the first one to post

Draxlr Reviews

Explore 6 Metabase Alternatives for Data Visualization and Analysis
Draxlr is an intuitive Metabase alternative, blending a robust no-code query builder with AI-powered SQL generation for both non-technical and advanced users. It seamlessly integrates with various databases and provides real-time alerts through Slack, email, and more. With features like embeddable dashboards, granular team access, customizable visualizations, and live data...
Source: www.draxlr.com
Explore 7 Tableau Alternatives for Data Visualization and Analysis
Draxlr is a no-code data visualization tool that simplifies creating dashboards and setting up alerts for SQL databases like PostgreSQL, MySQL, MS SQL, and more. It features an intuitive query builder for filtering, sorting, joining, summarizing, and grouping data without coding. Draxlr also supports advanced visualizations, embedded dashboards, and AI-driven insights, as...
Source: www.draxlr.com
5 best Looker alternatives
Draxlr: Draxlr is a modern self-service BI tool with AI integration capabilities that is built to ensure everyone in the team can easily find answers in raw data, and build actionable dashboards. Since it is one of the new tools, it can lack community support but is compensated by great customer support.
Source: www.draxlr.com
5 best dashboard building tools for SQL data in 2024
Draxlr is a modern self-serve business intelligence tool for growing businesses. Seamlessly connecting with multiple SQL databases, it transforms raw SQL data into polished dashboards effortlessly within minutes, eliminating the need for coding skills. Empowering users to effortlessly visualize and interpret data, Draxlr is tailored for modern business insights.
Source: www.draxlr.com

Social recommendations and mentions

Based on our record, Google Cloud Machine Learning seems to be a lot more popular than Draxlr. While we know about 33 links to Google Cloud Machine Learning, we've tracked only 1 mention of Draxlr. 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.

Google Cloud Machine Learning mentions (33)

  • Google Unveils Agent2Agent Protocol for Next-Gen AI Collaboration
    Google's introduction of new tools for building and managing multi-agent ecosystems through Vertex AI is a pivotal move for enterprises. The Agent Development Kit (ADK) is a notable feature, providing an open-source framework that allows users to create AI agents with fewer than 100 lines of code. This framework supports Python and integrates with the AI capabilities of Vertex AI. - Source: dev.to / 16 days ago
  • AI Innovations and Insights from Google Cloud Next 2025
    For further exploration, visit: Vertex AI Overview | Live API. - Source: dev.to / 17 days ago
  • Instrument your LLM calls to analyze AI costs and usage
    We use Vertex AI to simplify our implementation, to test different LLM providers and models, and to compare metrics such as cost, latency, errors, time to first token, etc, across models. - Source: dev.to / 20 days ago
  • Google Unveils Ironwood: 7th Gen TPU for Enhanced AI Inference
    Ironwood is part of Google's AI Hypercomputer architecture, a system optimized for AI workloads. This integrated supercomputing system leverages over a decade of AI expertise. It supports various frameworks such as Vertex AI and Pathways, enabling developers to utilize Ironwood effectively for distributed computing. - Source: dev.to / 21 days ago
  • Generating images with Gemini 2.0 Flash from Google
    Perhaps you're new to AI or wish to experiment with the Gemini API before integrating into an application. Using the Gemini API from Google AI is the best way for you to get started and get familiar with using the API. The free tier is also a great benefit. Then you can consider moving any relevant work over to Google Cloud/GCP Vertex AI for production. - Source: dev.to / 25 days ago
View more

Draxlr mentions (1)

What are some alternatives?

When comparing Google Cloud Machine Learning and Draxlr, you can also consider the following products

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

HistogramMaker.net - Create a Histogram for free with easy to use tools and download the Histogram as jpg, png or svg file. Customize Histogram according to your choice.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Canva - Canva is a graphic-design platform with a drag-and-drop interface to create print or visual content while providing templates, images, and fonts. Canva makes graphic design more straightforward and accessible regardless of skill level.

OpenCV - OpenCV is the world's biggest computer vision library

Microsoft Power BI - BI visualization and reporting for desktop, web or mobile

Loading...