Software Alternatives, Accelerators & Startups

Datameer VS PyTorch

Compare Datameer VS PyTorch and see what are their differences

Datameer logo Datameer

An all-in-one data transformation platform for exploring, preparing, visualizing, monitoring, and cataloging Snowflake insights.

PyTorch logo PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...
  • Datameer Landing page
    Landing page //
    2023-06-08

Datameer: Data Quality & Data Prep for Snowflake

Discover, explore, clean, transform, automate, and share Snowflake data with Datameer. The platform equips analysts and data engineers with a complete data toolset to efficiently prep their data.

Key Features:

  • Data catalog: Search and filter datasets using metadata for project-specific requirements.
  • Rapid Fire - No Code SQL Query Builder for data mining
  • Visual canvas-like interface: Easily design and maintain projects for seamless workflow.
  • Insights sharing: Share results and exceptions via Email or Slack with scheduled delivery options.
  • Seamless Snowflake integration: Deploy data assets to Snowflake with ease.
  • GIT version control: Automate version control and CI/CD for Snowflake data pipelines.
  • Materialization and dependency management: Ensure reliable data processing.
  • Cost and Usage Monitoring with drill down exploration
  • Data Quality Checks and Monitoring
  • API Framework for External Triggers
  • AI Support for Prep, Discovery, and Documentation
  • Production Job Scheduling Support and Dashboard
  • Automated Bi-Directional Cloud File Integration from and to AWS S3, Azure, and GCP

Benefits of Datameer Cloud:

  • Increased data accuracy and consistency.
  • Reduced data preparation time.
  • Improved data access and sharing.
  • Enhanced data-driven decision making.

Datameer is a Snowflake SELECT partner, recognized for its data preparation expertise. The platform prioritizes data security, with monitoring by Drata to protect your valuable data.

Unlock the power of your Snowflake insights with Datameer today.

  • PyTorch Landing page
    Landing page //
    2023-07-15

Datameer features and specs

  • Aggregate Transformations: Yes
  • Auto Documentation: Yes
  • Automated Email Notifications: Yes
  • BI integration: Yes
  • Data Catalog: Yes
  • Data Discovery: Yes
  • Data Preparation: Yes
  • Data Profiling: Yes
  • Data Transformation: Yes
  • Data Validation: Yes
  • Dataset Joins: Yes
  • Dependency Management: Yes
  • Deployment: Yes
  • Deployment History: Yes
  • Exploration: Yes
  • Extract and Split Function: Yes
  • Filter and Replace: Yes
  • Fresh Data: Yes
  • Full Lineage: Yes
  • Google Sheets Integration: Yes
  • Manage Columns Function: Yes
  • Materialization: Yes
  • Metadata Enrichment: Yes
  • Model Deployment: Yes
  • Monitoring: Yes
  • No Code Editor: Yes
  • Orchestration API: Yes
  • Pivot Table: Yes
  • Production Pipelines: Yes
  • Scheduling: Yes
  • Search: Yes
  • Sharing Insights: Yes
  • Slack Integration: Yes
  • Snowflake Catalog: Yes
  • Snowflake Native: Yes
  • SQL Code Editor: Yes
  • Version Control: Yes
  • AI Support for Prep, Discovery, and Documentation : Yes
  • Data Quality Monitoring: Yes
  • Cost and Usage Monitoring: Yes
  • Bi-Directional Cloud File Integration: Yes

PyTorch features and specs

No features have been listed yet.

Datameer videos

Datameer: Efficiently Extract Insights from Your Snowflake Data

PyTorch videos

PyTorch in 5 Minutes

More videos:

  • Review - Jeremy Howard: Deep Learning Frameworks - TensorFlow, PyTorch, fast.ai | AI Podcast Clips
  • Review - PyTorch at Tesla - Andrej Karpathy, Tesla

Category Popularity

0-100% (relative to Datameer and PyTorch)
Data Dashboard
100 100%
0% 0
Data Science And Machine Learning
Data Transformation
100 100%
0% 0
Data Science Tools
0 0%
100% 100

Questions and Answers

As answered by people managing Datameer and PyTorch.

Why should a person choose your product over its competitors?

Datameer's answer

  • Intuitive Visual Interface: Datameer offers a user-friendly visual interface for easy data prep with or without coding.

  • Seamless Snowflake Integration: Datameer integrates seamlessly with Snowflake, keeping all of your data in Snowflake where it should be.

  • Streamlined Data Analytics: With Datameer and Snowflake, you can unlock valuable insights faster and more efficiently, eliminating complex coding and cumbersome data transformations.

What's the story behind your product?

Datameer's answer

The story of Datameer began with a vision to democratize data analytics. The founders recognized the growing need for a platform that could empower organizations to leverage their data effectively, regardless of their technical expertise.

They set out to create a solution that would bridge the gap between data science and business users, enabling anyone to make data-driven decisions.

Over the years, Datameer has evolved into a leading data preparation and analytics platform, trusted by organizations across various industries to transform raw data into valuable insights.

Who are some of the biggest customers of your product?

Datameer's answer

Datameer caters to businesses of all sizes, from small businesses to large enterprises. Some of it's most prominent customers include BT Openreach, Vivint, BMO Financial Group, Akbank, Skylar, and Reliant Funding. These companies use Datameer's data preparation and analytics platform to make better decisions with their data.

Which are the primary technologies used for building your product?

Datameer's answer

Snowflake - The Data Cloud

What makes your product unique?

Datameer's answer

Datameer offers an intuitive and user-friendly data transformation and analytics platform. Unlike other solutions that require extensive SQL knowledge, Datameer allows users to work with complex data easily through a visual interface. Whether you're a data engineer or a business analyst, Datameer empowers you to derive meaningful insights from your data without requiring extensive SQL skills.

How would you describe your primary audience?

Datameer's answer

Datameer caters to a diverse audience consisting of both technical and non-technical users. Data engineers and data analysts benefit from the platform's powerful data processing capabilities and advanced analytics functionalities. At the same time, business users, such as marketing professionals or operations managers, appreciate the simplicity and accessibility of Datameer's interface, allowing them to explore and visualize data without relying on IT or data science teams.

In essence, Datameer's primary audience is anyone who wants to unlock the value of their data quickly and efficiently.

User comments

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Reviews

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

Datameer Reviews

We have no reviews of Datameer yet.
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PyTorch Reviews

10 Python Libraries for Computer Vision
Similar to TensorFlow and Keras, PyTorch and torchvision offer powerful tools for computer vision tasks. PyTorch’s dynamic computation graph and torchvision’s datasets and pre-trained models make it easy to implement tasks such as image classification, object detection, and style transfer.
Source: clouddevs.com
25 Python Frameworks to Master
Along with TensorFlow, PyTorch (developed by Facebook’s AI research group) is one of the most used tools for building deep learning models. It can be used for a variety of tasks such as computer vision, natural language processing, and generative models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
PyTorch is another open-source machine learning framework that is widely used in academia and industry. PyTorch provides excellent support for building deep learning models, and it has several pre-trained models for computer vision tasks, making it the ideal tool for several computer vision applications. PyTorch offers a user-friendly interface that makes it easier for...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
When we compare HuggingFace model availability for PyTorch vs TensorFlow, the results are staggering. Below we see a chart of the total number of models available on HuggingFace that are either PyTorch or TensorFlow exclusive, or available for both frameworks. As we can see, the number of models available for use exclusively in PyTorch absolutely blows the competition out of...
15 data science tools to consider using in 2021
First released publicly in 2017, PyTorch uses arraylike tensors to encode model inputs, outputs and parameters. Its tensors are similar to the multidimensional arrays supported by NumPy, another Python library for scientific computing, but PyTorch adds built-in support for running models on GPUs. NumPy arrays can be converted into tensors for processing in PyTorch, and vice...

Social recommendations and mentions

Based on our record, PyTorch seems to be a lot more popular than Datameer. While we know about 109 links to PyTorch, we've tracked only 3 mentions of Datameer. 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.

Datameer mentions (3)

  • Alteryx Freelancers - How Much Are You Taking Home Hourly?
    Hence the popularity of tools like Alteryx... There are newer better tool now like datameer.com easier to use and more modern. Source: over 2 years ago
  • Alteryx - worth the time investment to learn?
    That's right... Just look at datameer.com it's SaaS so much easier to handover... And much cheaper too... Source: over 2 years ago
  • Alteryx - worth the time investment to learn?
    I am biased but check out: datameer.com. Source: over 2 years ago

PyTorch mentions (109)

  • Understanding GPT: How To Implement a Simple GPT Model with PyTorch
    In this guide, we provided a comprehensive, step-by-step explanation of how to implement a simple GPT (Generative Pre-trained Transformer) model using PyTorch. We walked through the process of creating a custom dataset, building the GPT model, training it, and generating text. This hands-on implementation demonstrates the fundamental concepts behind the GPT architecture and serves as a foundation for more complex... - Source: dev.to / 5 days ago
  • Building a Simple Chatbot using GPT model - part 2
    PyTorch is a powerful and flexible deep learning framework that offers a rich set of features for building and training neural networks. - Source: dev.to / 14 days ago
  • Clusters Are Cattle Until You Deploy Ingress
    Oddly enough, sometimes, the best way to learn is by putting forth incorrect opinions or questions. Recently, while wrestling with AI project complexities, I pondered aloud whether all Docker images with AI models would inevitably be bulky due to PyTorch dependencies. To my surprise, this sparked many helpful responses, offering insights into optimizing image sizes. Being willing to be wrong opens up avenues for... - Source: dev.to / 7 days ago
  • My Favorite DevTools to Build AI/ML Applications!
    TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more... - Source: dev.to / about 1 month ago
  • Functions and operators for Dot and Matrix multiplication and Element-wise calculation in PyTorch
    *My post explains Dot, Matrix and Element-wise multiplication in PyTorch. - Source: dev.to / 3 months ago
View more

What are some alternatives?

When comparing Datameer and PyTorch, you can also consider the following products

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.

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.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

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