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Metabase VS TensorFlow

Compare Metabase VS TensorFlow and see what are their differences

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. featured
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Metabase logo Metabase

Metabase is the easy, open source way for everyone in your company to ask questions and learn from...

TensorFlow logo 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.
  • Metabase Landing page
    Landing page //
    2024-10-22
  • TensorFlow Landing page
    Landing page //
    2023-06-19

Metabase features and specs

  • Ease of Use
    Metabase offers an intuitive and user-friendly interface, which makes it easy for non-technical users to generate and analyze reports without requiring SQL knowledge.
  • Open Source
    Being open-source, Metabase allows organizations to customize and extend the tool according to their needs, and it can be self-hosted to retain full control over data.
  • Quick Setup
    Deploying Metabase is straightforward and can be accomplished quickly, enabling teams to start analyzing data almost immediately.
  • Integrations
    Metabase integrates with a wide array of databases and data sources, making it versatile for organizations with diverse data environments.
  • Visualization Options
    It provides a variety of visualization options, from simple charts to complex dashboards, to help users better understand their data.
  • Community Support
    As an open-source project, Metabase has a strong community that contributes to its development and offers support through forums and documentation.
  • Embedded Analytics
    Metabase offers an embedded analytics feature which allows organizations to integrate dashboards and reports into their own applications.

Possible disadvantages of Metabase

  • Limited Advanced Analytics
    While great for basic reporting, Metabase lacks some of the advanced analytics capabilities offered by more specialized BI tools.
  • Scaling Issues
    Metabase might face performance issues as data volume and user base grow, making it less suitable for very large-scale deployments without significant optimization.
  • Customization Limitations
    Even though Metabase is open-source, some users find its customization options limited compared to other BI tools, especially regarding dashboard design.
  • Security Features
    The platform's security features are not as robust as those of some enterprise-level BI tools, potentially requiring additional measures for highly sensitive data.
  • Dependency on Third-Party Services
    For certain features, Metabase may rely on third-party services, which could introduce additional points of failure and dependency.
  • Limited Collaboration Tools
    Collaboration features are somewhat basic compared to those offered by more comprehensive BI platforms, possibly making teamwork less efficient.
  • No Mobile App
    Metabase does not offer a dedicated mobile app, which could be a limitation for users who need to access dashboards and reports on the go.

TensorFlow features and specs

  • Comprehensive Ecosystem
    TensorFlow offers a complete ecosystem for end-to-end machine learning, covering everything from data preprocessing, model building, training, and deployment to production.
  • Community and Support
    TensorFlow boasts a large and active community, as well as extensive documentation and tutorials, making it easier for beginners to learn and experts to get help.
  • Flexibility
    TensorFlow supports a wide range of platforms such as CPUs, GPUs, TPUs, mobile devices, and embedded systems, providing flexibility depending on the user's needs.
  • Integrations
    TensorFlow integrates well with other Google products and services, including Google Cloud, facilitating seamless deployment and scaling.
  • Versatility
    TensorFlow can be used for a wide range of applications from simple neural networks to more complex projects, including deep learning and artificial intelligence research.

Possible disadvantages of TensorFlow

  • Complexity
    TensorFlow can be challenging to learn due to its complexity and the steep learning curve, particularly for beginners.
  • Performance Overhead
    Although TensorFlow is powerful, it can sometimes exhibit performance overhead compared to other, lighter frameworks, leading to longer training times.
  • Verbose Syntax
    The code in TensorFlow tends to be more verbose and less intuitive, which can make writing and debugging code more cumbersome relative to other frameworks like PyTorch.
  • Compatibility Issues
    Frequent updates and changes can lead to compatibility issues, requiring significant effort to keep libraries and dependencies up to date.
  • Mobile Deployment
    While TensorFlow supports mobile deployment, it is less optimized for mobile platforms compared to some other specialized frameworks, leading to potential performance drawbacks.

Analysis of Metabase

Overall verdict

  • Overall, Metabase is a solid choice for businesses seeking an intuitive and powerful business intelligence tool. Its combination of ease of use, functionality, and cost-effectiveness makes it a popular option among small to medium-sized enterprises as well as larger organizations looking to empower their teams with data-driven insights.

Why this product is good

  • Metabase is considered good due to its user-friendly interface, which allows non-technical users to create and share dashboards and reports easily. It integrates seamlessly with various data sources and provides a flexible query builder for more advanced data analysis. Additionally, it offers an open-source version, which can be a cost-effective solution for organizations looking to implement business intelligence tools without incurring high expenses.

Recommended for

  • Small to medium-sized businesses looking for a budget-friendly BI tool
  • Teams with limited technical expertise who still need to access and analyze data
  • Organizations looking for open-source business intelligence solutions
  • Companies that require a tool that can quickly integrate with existing data sources

Metabase videos

+ Add

What is Metabase?

More videos:

  • Demo - See Metabase in action in 5 mins
  • Review - Metabase vs Apache Superset: Which is best for your team?
  • Review - Metabase vs Tableau: Which is better for your team
  • Review - Metabase vs. Looker: Which is best for your team?

TensorFlow videos

+ Add

What is Tensorflow? - Learn Tensorflow for Machine Learning and Neural Networks

More videos:

  • Tutorial - TensorFlow In 10 Minutes | TensorFlow Tutorial For Beginners | Deep Learning & TensorFlow | Edureka
  • Review - TensorFlow in 5 Minutes (tutorial)

Category Popularity

0-100% (relative to Metabase and TensorFlow)

Metabase

TensorFlow

Data Dashboard
100 100%
Data Dashboard
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Data Visualization
100 100%
Data Visualization
0% 0
AI
0 0%
AI
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Metabase and TensorFlow

Metabase 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
5 best Looker alternatives
Metabase: Metabase is an open-source BI tool that offers a free self-hosted plan, but this can be challenging for non-technical users who may struggle with setup and maintenance. While the cloud-hosted option simplifies that, it comes at a higher cost, which might not be ideal for smaller teams or businesses.
Source: www.draxlr.com
10 Best Alternatives to Looker in 2024
Metabase: Metabase is a popular open-source alternative known for its cost-effectiveness and ease of setup. Its simplicity and straightforward deployment make it particularly appealing to smaller businesses and startups.
Source: www.sigmacomputing.com
6 Best Looker alternatives
If you’re considering Metabase, take a look at our deepdive into Looker vs Metabase, as well as a breakdown of top Metabase alternatives.
Source: trevor.io
10 Best Looker Alternatives in 2024 | A Practitioner Review
While Metabase may not offer the same depth in modeling features or the proprietary semantic layer (LookML) that Looker does, it can integrate with Cube.dev to provide a viable, modern, open-source alternative. Additionally, Metabase's alert feature and its general adequacy for IT-related reporting present a valuable, lightweight solution for teams not requiring the full...
Source: www.holistics.io

TensorFlow Reviews

7 Best Computer Vision Development Libraries in 2024
From the widespread adoption of OpenCV with its extensive algorithmic support to TensorFlow's role in machine learning-driven applications, these libraries play a vital role in real-world applications such as object detection, facial recognition, and image segmentation.
Source: www.labellerr.com
10 Python Libraries for Computer Vision
TensorFlow and Keras are widely used libraries for machine learning, but they also offer excellent support for computer vision tasks. TensorFlow provides pre-trained models like Inception and ResNet for image classification, while Keras simplifies the process of building, training, and evaluating deep learning models.
Source: clouddevs.com
25 Python Frameworks to Master
Keras is a high-level deep-learning framework capable of running on top of TensorFlow, Theano, and CNTK. It was developed by François Chollet in 2015 and is designed to provide a simple and user-friendly interface for building and training deep learning models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
TensorFlow is an open-source software library for dataflow and differentiable programming across a range of tasks such as machine learning, computer vision, and natural language processing. It provides excellent support for deep learning models and is widely used in several industries. TensorFlow offers several pre-trained models for image classification, object detection,...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
There are a couple of notable exceptions to this rule, the most notable being that those in Reinforcement Learning should consider using TensorFlow. TensorFlow has a native Agents library for Reinforcement Learning, and Deepmind’s Acme framework is implemented in TensorFlow. OpenAI’s Baselines model repository is also implemented in TensorFlow, although OpenAI’s Gym can be...
Source: www.assemblyai.com

Social recommendations and mentions

Based on our record, Metabase should be more popular than TensorFlow. It has been mentiond 17 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.

Metabase mentions (17)

  • Ask HN: Who is hiring? (April 2025)
    Metabase | https://metabase.com/ | Remote (Global) | Full-time | Applied AI Engineers, Engineering Managers, Frontend and Backend Engineers Metabase is an open source (https://github.com/metabase/metabase) business intelligence software that lets anyone in your company rummage around in the databases you have. It connects to a number of databases / data warehouses (BigQuery, Redshift, Snowflake, Postgres, MySQL,... - Source: Hacker News / 2 months ago
  • Ask HN: Who is hiring? (September 2024)
    Metabase | https://metabase.com | REMOTE | Full-time | Backend Engineers, Frontend Engineers, and Engineering Managers Metabase is open source analytics software that lets anyone in your company rummage around in the databases you have. It connects to a number of databases / data warehouses (BigQuery, Redshift, Snowflake, Postgres, MySQL, etc). People rather like the product (https://metabase.com/love). We're a... - Source: Hacker News / 10 months ago
  • Tools for Starting a Business or Testing an Idea: A Beginner's Guide
    Reporting - Metabase A free, open-source business intelligence tool that helps you create custom reports and dashboards to track your business metrics and make data-driven decisions. - Source: dev.to / 10 months ago
  • Is Tableau Dead?
    I've never used Tableau, but heard a lot of hate about it. However, in my previous role, we were big fans of Metabase (https://metabase.com). You can also self-host it, which was a huge win for us. - Source: Hacker News / over 1 year ago
  • Ask HN: Open-Source Self-Hosted No-Code Platforms?
    The solution really depends on what sort of problems you are trying to solve and who your customers are. There are a fair few low-code solutions out there for reporting and data visualisation that are great for finance and marketing teams for example. e.g. https://metabase.com/ , https://evidence.dev/ For enterprise processes I'd go with Camunda (solely based on recommendations and not first hand experience).... - Source: Hacker News / about 2 years ago
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TensorFlow mentions (7)

  • Creating Image Frames from Videos for Deep Learning Models
    Converting the images to a tensor: Deep learning models work with tensors, so the images should be converted to tensors. This can be done using the to_tensor function from the PyTorch library or convert_to_tensor from the Tensorflow library. - Source: dev.to / over 2 years ago
  • Need help with a Tensorflow function
    So I went to tensorflow.org to find some function that can generate a CSR representation of a matrix, and I found this function https://www.tensorflow.org/api_docs/python/tf/raw_ops/DenseToCSRSparseMatrix. Source: almost 3 years ago
  • Help: Slow performance with windows 10 compared to Ubuntu 20.04 with TF2.7
    Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env. Source: about 3 years ago
  • [Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
    I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: about 3 years ago
  • [Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
    I have looked at this TensorFlow website and TensorFlow.org and some of the examples are written by others, and it seems that I am stuck in RNNs. What is the best way to install TensorFlow, to follow the documentation and learn the methods in RNNs in Python? Is there a good tutorial/resource? Source: about 3 years ago
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What are some alternatives?

When comparing Metabase and TensorFlow, you can also consider the following products

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

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

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

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

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