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Fivetran VS PyTorch

Compare Fivetran VS PyTorch and see what are their differences

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Fivetran logo Fivetran

Fivetran offers companies a data connector for extracting data from many different cloud and database sources.

PyTorch logo PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...
  • Fivetran Landing page
    Landing page //
    2023-09-19
  • PyTorch Landing page
    Landing page //
    2023-07-15

Fivetran

Website
fivetran.com
Pricing URL
Official Fivetran Pricing
$ Details
-
Release Date
2012 January
Startup details
Country
United States
State
California
City
Oakland
Founder(s)
George Fraser
Employees
250 - 499
Edit details

PyTorch

Website
pytorch.org
Pricing URL
-
$ Details
Release Date
-
Edit details

Fivetran features and specs

  • Automation
    Fivetran automates data integration, eliminating the need for manual coding and reducing maintenance overhead.
  • Scalability
    Fivetran can easily scale its services to handle growing data loads, making it suitable for businesses of various sizes.
  • Wide Range of Connectors
    It supports a broad array of data sources and destinations, allowing for diverse data pipelines.
  • Data Transformation
    Fivetran provides built-in data transformation capabilities, ensuring that data is in the correct format when it reaches the destination.
  • Real-Time Data Syncing
    Fivetran allows for near real-time data syncing, which is crucial for businesses that rely on up-to-date data for decision-making.
  • Reliability
    The service ensures data integrity and reliability, minimizing data loss during transfers.

Possible disadvantages of Fivetran

  • Cost
    Fivetran can be expensive, especially for small businesses or startups with limited budgets.
  • Limited Customization
    The platform offers limited options for customization, which might be a drawback for businesses with unique data integration needs.
  • Complex Setup for Non-Technical Users
    Despite its automation features, the initial setup can be complex for users without technical expertise.
  • Dependency on Third-Party Services
    Reliance on Fivetran means depending on a third party for crucial data integration tasks, which could be risky if the service faces downtime.
  • Data Latency for Some Sources
    While Fivetran supports near real-time syncing for many sources, some data sources might experience latency, affecting the freshness of the data.

PyTorch features and specs

  • Dynamic Computation Graph
    PyTorch uses a dynamic computation graph, which allows for interactive and flexible model building. This is particularly beneficial for researchers who need to modify the network architecture on-the-fly.
  • Pythonic Nature
    PyTorch is designed to be deeply integrated with Python, making it very intuitive for Python developers. The framework feels more 'native' to Python, which improves the ease of learning and use.
  • Strong Community Support
    PyTorch has a large, active, and growing community. This means abundant resources such as tutorials, forums, and third-party tools are available to help developers solve problems and share solutions.
  • Flexibility and Control
    PyTorch offers granular control over computations and provides extensive debugging capabilities. This level of control is beneficial for tasks that require precise tuning and custom implementations.
  • Support for GPU Acceleration
    PyTorch offers seamless integration with GPU hardware, which significantly accelerates the computation process. This makes it highly efficient for deep learning tasks.
  • Rich Ecosystem
    PyTorch has a rich ecosystem including libraries like torchvision, torchaudio, and torchtext, which are specialized for different data types and can significantly shorten development times.

Possible disadvantages of PyTorch

  • Limited Production Deployment Tools
    PyTorch is primarily designed for research rather than production. While deployment tools like TorchServe exist, they are not as mature or integrated as solutions offered by other frameworks like TensorFlow.
  • Lesser Adoption in Industry
    While PyTorch is popular among researchers, it has historically seen less adoption in industry compared to TensorFlow, which means there might be fewer resources for large-scale production deployments.
  • Inconsistent API Changes
    As PyTorch continues to evolve rapidly, occasionally there are breaking changes or inconsistent API updates. This can create maintenance challenges for existing codebases.
  • Steeper Learning Curve for Beginners
    Despite its Pythonic design, PyTorch's focus on flexibility and control can make it slightly harder for beginners to get started compared to some other high-level libraries and frameworks.
  • Less Mature Documentation
    Although the documentation is improving, it has been historically less comprehensive and mature compared to other frameworks like TensorFlow, which can make it difficult to find detailed, clear information.

Analysis of Fivetran

Overall verdict

  • Fivetran is generally regarded as a good solution for businesses looking for an automated, reliable, and easy-to-use data integration tool. It is particularly beneficial for companies that wish to reduce time and effort spent on managing data pipelines and ensuring accurate data transfer.

Why this product is good

  • Fivetran is considered good due to its ability to automate data integration processes, providing a seamless and efficient way to connect various data sources to your data warehouse. It offers pre-built connectors, automated schema management, and reliable data syncing, which reduces the need for manual coding and maintenance. Its robust security measures and scalability also contribute to its positive reputation.

Recommended for

    Fivetran is recommended for small to large businesses that require efficient data integration from multiple sources into their data warehouse. It is ideal for organizations looking for a fully managed service to simplify their ETL/ELT processes, especially those using cloud-based data warehousing solutions such as Snowflake, BigQuery, or Redshift.

Analysis of PyTorch

Overall verdict

  • Yes, PyTorch is considered a good deep learning framework.

Why this product is good

  • Ease of Use: PyTorch has an intuitive interface that makes it easier to learn and use, especially for beginners.
  • Dynamic Computation Graphs: PyTorch employs dynamic computation graphs, which provide more flexibility in building and modifying models on the fly.
  • Strong Community and Support: PyTorch has a large and active community, offering extensive resources, forums, and tutorials.
  • Research Adoption: PyTorch is widely adopted in the research community, making state-of-the-art models and techniques readily available.
  • Integration: PyTorch integrates well with other libraries and tools in the Python ecosystem, providing robust support for various applications.

Recommended for

  • Researchers and Academics: Ideal for those who need a flexible and dynamic tool for experimenting with new models and techniques.
  • Industry Practitioners: Suitable for developers and data scientists working on production-level machine learning solutions.
  • Educators and Learners: Great for educational purposes due to its easy-to-understand syntax and comprehensive documentation.

Fivetran videos

+ Add

Cloud Data Warehouse Benchmark Redshift vs Snowflake vs BigQuery | Fivetran

More videos:

  • Review - Looker + Fivetran: Data Source to Dashboard in an Afternoon
  • Review - The Modern Data Stack: Fivetran + Looker + Snowflake

PyTorch videos

+ Add

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 Fivetran and PyTorch)

Fivetran

PyTorch

Data Integration
100 100%
Data Integration
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
ETL
100 100%
ETL
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Fivetran and PyTorch. For example, how are they different and which one is better?
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Reviews

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

Fivetran Reviews

Best ETL Tools: A Curated List
High costs: Fivetran’s pricing model, based on Monthly Active Rows (MAR), is one of the most expensive modern ELT vendors, often 5-10x the alternatives. Fivetran measures MARs based on its internal representation of data. Costs are especially high with connectors that need to download all source data each time or that have nonrelational data because Fivetran converts it into...
Source: estuary.dev
Top 11 Fivetran Alternatives for 2024
Fivetran's pricing is determined by monthly active rows (MAR), which can be unpredictable because of the way Fivetran internally represents data and manages non-relational sources. Additionally, reducing latency significantly increases costs. While a small deployment (2M MARs/month) can cost $700-$2667, 10M MARs/month get you into $10K a month. It is not unheard of for...
Source: estuary.dev
10 Best ETL Tools (October 2023)
It is a cloud-based ETL solution that supports data integration with data warehouses like Redshift, BigQuery, Azure, and Snowflake. One of the top selling points of Fivetran is its array of data sources, with nearly 90 possible SaaS sources and the ability to add custom integrations.
Source: www.unite.ai
15+ Best Cloud ETL Tools
Fivetran is a cloud-based automated ETL tool that simplifies the process of transporting data from various sources to a database or data warehouse. It offers an array of more than 200 connectors to help you to collect data seamlessly from multiple sources at the same time.
Source: estuary.dev
Top 14 ETL Tools for 2023
Overall, Fivetran is a great ETL solution for businesses looking to streamline their data integration process. The platform makes it easy for organizations of any size to move and transform data from multiple sources into an analytics-ready form quickly and cost-effectively. While there have been some issues reported with Fivetran’s customer service and pricing model, the...
Source: www.integrate.io

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...
Source: www.assemblyai.com
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...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, PyTorch seems to be a lot more popular than Fivetran. While we know about 133 links to PyTorch, we've tracked only 12 mentions of Fivetran. 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.

Fivetran mentions (12)

  • Sync Snowflake and Google Sheets
    Even looking past these limitations, internal scripts invariably require development and maintenance time, and as any developer knows, can break at the worst of times :) Method #2: Use Zapier? (https://zapier.com) Want to use Zapier to do this? You can’t. Not only because it doesn’t track deletes, updates to existing records, and only does one way syncs. But because Snowflake isn’t supported. Method #3:... - Source: Hacker News / over 2 years ago
  • Big problem with companies now is they hire data scientist for task that don't require data science practices.
    Disclaimer: I work for Fivetran, a data integration company. Source: almost 3 years ago
  • I love data science but hate data engineering
    Disclaimer: I'm a product evangelist for a data integration company called Fivetran, so I'm shamelessly shilling here. Source: almost 3 years ago
  • Which webflow theme is this?
    I really like the theme they’re using on https://fivetran.com. Source: about 3 years ago
  • A modern data stack for startups
    From experience then, believe me when I say you don't want to build these. Thankfully, ETL products like Fivetran and Stitch run and maintain these extraction processes for you. - Source: dev.to / about 3 years ago
View more

PyTorch mentions (133)

  • Grasping Computer Vision Fundamentals Using Python
    To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isn’t just a tool, it’s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that don’t just interpret visuals, but... - Source: dev.to / about 1 month ago
  • Top Programming Languages for AI Development in 2025
    With the quick emergence of new frameworks, libraries, and tools, the area of artificial intelligence is always changing. Programming language selection. We're not only discussing current trends; we're also anticipating what AI will require in 2025 and beyond. - Source: dev.to / about 2 months ago
  • Fine-tuning LLMs locally: A step-by-step guide
    Next, we define a training loop that uses our prepared data and optimizes the weights of the model. Here's an example using PyTorch:. - Source: dev.to / 2 months ago
  • 10 Must-Have AI Tools to Supercharge Your Software Development
    8. TensorFlow and PyTorch: These frameworks support AI and machine learning integrations, allowing developers to build and deploy intelligent models and workflows. TensorFlow is widely used for deep learning applications, offering pre-trained models and extensive documentation. PyTorch provides flexibility and ease of use, making it ideal for research and experimentation. Both frameworks support neural network... - Source: dev.to / 4 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    Frameworks like TensorFlow and PyTorch can help you build and train models for various tasks, such as risk scoring, anomaly detection, and pattern recognition. - Source: dev.to / 4 months ago
View more

What are some alternatives?

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

Stitch - Consolidate your customer and product data in minutes

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.

Hevo Data - Hevo Data is a no-code, bi-directional data pipeline platform specially built for modern ETL, ELT, and Reverse ETL Needs. Get near real-time data pipelines for reporting and analytics up and running in just a few minutes. Try Hevo for Free today!

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

Talend Data Integration - Talend offers open source middleware solutions that address big data integration, data management and application integration needs for businesses of all sizes.

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

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