Software Alternatives, Accelerators & Startups

Minio VS TensorFlow

Compare Minio VS TensorFlow and see what are their differences

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.

Minio logo Minio

Minio is an open-source minimal cloud storage server.

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.
  • Minio Landing page
    Landing page //
    2023-09-25
  • TensorFlow Landing page
    Landing page //
    2023-06-19

Minio features and specs

  • High Performance
    Minio is designed for high-performance object storage, providing fast read and write speeds and scalability for large-scale storage needs.
  • Open Source
    Being an open-source platform, Minio allows users to review, modify, and distribute its code, fostering transparency and collaboration within the community.
  • S3 Compatibility
    Minio offers S3 API compatibility, making it easier to integrate with existing applications and tools that are already designed to work with AWS S3.
  • Lightweight
    Minio is extremely lightweight and can be deployed on minimal hardware, making it an efficient option for edge computing and low-resource environments.
  • Multi-Cloud Support
    Minio supports a variety of cloud environments, allowing for flexibility and ease of data distribution across multiple cloud providers.
  • Strong Security
    Minio offers strong security features such as automatic encryption, Identity and Access Management (IAM), and compliance with enterprise-level security standards.

Possible disadvantages of Minio

  • Learning Curve
    For beginners, initial setup and configuration can be complex, requiring a certain level of technical expertise to deploy and manage effectively.
  • Limited Ecosystem
    Compared to AWS S3, Minio has a relatively smaller ecosystem of integrated tools and services, which could limit functionality or require additional development resources.
  • Community Support
    While there is a growing community around Minio, the support channels and community contributions are not as extensive as those for more established platforms like AWS.
  • Feature Parity
    Although Minio offers many similar features to AWS S3, there are still some advanced features and services in AWS that are not available in Minio.

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.

Minio videos

This is MinIO

More videos:

  • Review - A Review of MinIO's Performance Benchmarks
  • Review - MinIO Hardware Considerations

TensorFlow videos

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 Minio and TensorFlow)
Cloud Storage
100 100%
0% 0
Data Science And Machine Learning
Cloud Computing
100 100%
0% 0
AI
0 0%
100% 100

User comments

Share your experience with using Minio and TensorFlow. 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 Minio and TensorFlow

Minio Reviews

ReductStore vs. MinIO & InfluxDB on LTE Network: Who Really Wins the Speed Race?
Maintaining consistency between multiple databases, like MinIO and InfluxDB, adds a layer of complexity. In our setup, MinIO, used for blob storage, is linked to data points in InfluxDB via its filename. Any inconsistencies or mismatches between the two could potentially result in data loss. Furthermore, we need to query both databases, which is quite inefficient. Lastly,...
Performance comparison: ReductStore vs. Minio
We often use blob storage like S3, if we need to store data of different formats and sizes somewhere in the cloud or in our internal storage. Minio is an S3 compatible storage which you can run on your private cloud, bare-metal server or even on an edge device. You can also adapt it to keep historical data as a time series of blobs. The most straightforward solution would be...
Best & Cheapest Object Storage Providers With S-3 Support
MinIO supports many use cases for diverse settings and has been cloud-native from its inception. MinIO’s software-defined suite operates in public and private clouds smoothly at the edge and positions itself as a leader in hybrid cloud object storage.
Source: macpost.net
What are the alternatives to S3?
Zenko is an open source multi-cloud controller allowing users to be in control of data while leveraging the efficiency of private and public clouds. Zenko stores information locally and to Amazon S3, Azure Blob storage, Google Cloud Storage, or any S3-compatible cloud storage platform (Ceph, Minio, and more). Zenko, as described on the official website, is not a data mover,...
Source: www.w6d.io
Ceph Storage Platform Alternatives in 2022
MinIO leverages the hard won knowledge of the web scalers to bring a simple scaling model to object storage. At MinIO, scaling starts with a single cluster which can be federated with other MinIO clusters to create a global namespace, spanning multiple data centers if needed. It is one of the reasons that more than half the Fortune 500 runs MinIO.

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.
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...

Social recommendations and mentions

Based on our record, Minio seems to be a lot more popular than TensorFlow. While we know about 167 links to Minio, we've tracked only 7 mentions of TensorFlow. 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.

Minio mentions (167)

  • OpenBSD Upgrade 7.6 to 7.7
    In addition, it also includes MariaDB update where "Binary logs are no longer purged by default unless a replica has connected", and minio update where "the MinIO Gateway and the related filesystem mode code have been removed". - Source: dev.to / 16 days ago
  • Hosting Services – The Short and Mid-Term Solution Before Transition to the Public Cloud
    Consume object storage – a hosting provider can deploy and maintain object storage services (such as Min.io), offering his customers to begin consuming storage capabilities that exist in cloud-native environments. - Source: dev.to / 3 months ago
  • When using an S3-compatible Object Storage, be cautious when upgrading **SDK for Java 2.x** to version **2.30.0 or later**
    Based on a rough check using o1 pro mode & Deep Search, MinIO supports it, but other storages do not. - Source: dev.to / 3 months ago
  • Gitlab names Bill Staples as new CEO
    You don't happen to work at Minio do you? Because apparently Minio is for AI these days: https://min.io/. - Source: Hacker News / 5 months ago
  • Minio integration with nestjs | file upload & retrieve
    What is minio? Minio is *free, open-source, scalable S3 compatible object storage. - Source: dev.to / 6 months ago
View more

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: almost 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
View more

What are some alternatives?

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

Ceph - Ceph is a distributed object store and file system designed to provide excellent performance...

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

Google Cloud Storage - Google Cloud Storage offers developers and IT organizations durable and highly available object storage.

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

Azure Blob Storage - Use Azure Blob Storage to store all kinds of files. Azure hot, cool, and archive storage is reliable cloud object storage for unstructured data

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