Software Alternatives, Accelerators & Startups
Register | Login

NewRelic VS PyTorch

Compare NewRelic VS PyTorch and see what are their differences

Mixo
AI-powered website builder that helps you create professional sites in minutes 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

NewRelic logo NewRelic

New Relic is a Software Analytics company that makes sense of billions of metrics across millions of apps. We help the people who build modern software understand the stories their data is trying to tell them.

PyTorch logo PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...
  • NewRelic Landing page
    Landing page //
    2023-10-05
  • PyTorch Landing page
    Landing page //
    2023-07-15

NewRelic features and specs

  • Comprehensive Monitoring
    New Relic provides a wide range of monitoring capabilities including application performance, infrastructure, and real user monitoring, offering a holistic view of your system's health.
  • Real-Time Data
    New Relic offers real-time analytics and insights, enabling quick identification and resolution of issues as they occur.
  • Advanced Alerting
    New Relic's advanced alerting system allows you to set customizable thresholds and get notified through various channels, helping to proactively manage potential issues.
  • User-Friendly Interface
    The platform features an intuitive, user-friendly interface that makes it easy to navigate and visualize data, even for less experienced users.
  • Integration Capabilities
    New Relic integrates seamlessly with many other tools and platforms, making it easy to incorporate into existing workflows.
  • Scalability
    Whether you have a small startup or a large enterprise, New Relic scales easily with your growing needs.
  • Comprehensive Documentation and Support
    New Relic offers extensive documentation and a variety of support options including forums, customer support, and a vibrant community.

Possible disadvantages of NewRelic

  • Cost
    New Relic can be expensive, especially for smaller businesses or startups that may not have a large budget for monitoring tools.
  • Complexity
    While New Relic offers a lot of features, it can also be complex to set up and configure, requiring significant time and expertise.
  • Performance Impact
    In some cases, the agents and monitoring tools can add overhead to the monitored systems, potentially affecting performance.
  • Data Storage Limits
    Lower-tier plans come with limits on data retention and storage, which may not be sufficient for some businesses with high data requirements.
  • Steep Learning Curve
    The breadth of features and capabilities can result in a steep learning curve for new users, making it challenging to fully leverage the platform's potential quickly.

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.

NewRelic videos

No NewRelic videos yet. You could help us improve this page by suggesting one.

Add video

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 NewRelic and PyTorch)

NewRelic

PyTorch

Monitoring Tools
100 100%
Monitoring Tools
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Performance Monitoring
100 100%
Performance Monitoring
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using NewRelic and PyTorch. 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 NewRelic and PyTorch

NewRelic Reviews

New Relic vs. Scout: Which Is The Right APM For You?
The top portion of the page is similar between New Relic and Scout: a breakdown of time spent by category (ex: Ruby, Database, External HTTP services, etc) over time. You can view data across similar timeframes in both Scout and New Relic (New Relic offers three months of data in their Pro package and Scout can do the same in their custom plans).
Source: scoutapm.com
Best New Relic Alternatives for Application Performance Monitoring (Cloud & SaaS)
Pingdom Server Monitor, which was formerly Scout Server Monitoring App which was acquired by Pingdom, has superior performance to New Relic, in particular when comparing response times, as seen in comparisons below. Ping Server Monitor comes ahead of New Relic in almost every single Response Time test and benchmark, beating it by almost 20x in terms of overhead.
Source: www.ittsystems.com
10 Best Application Monitoring Tools for all Platforms
The NewRelic is a one of the best application performance management and monitoring software that gives you a deep analysis to the app stack. New Relic offers a real-time status checking of the app’s availability. It also gives email alerts and real-time notification.
Source: www.technig.com
Best DataDog Alternatives, Replacements & Competitors for Application & Log Monitoring
New Relic is an application/infrastructure performance management software designed for DevOps. The basic platform gives you real-time insights on the full stack of your cloud apps and infrastructure. New Relic can keep track of your apps whether is on-premises, on the cloud, or in hybrid environments.
Source: www.pcwdld.com
Top 15 Website Monitoring Tools
New Relic is very well known in the performance and developer community for providing a lot of different features and has been around since 2008. New Relic gives you deep performance analytics for every part of your software environment. You can easily view and analyze massive amounts of data, and gain actionable insights in real time. They do provide uptime alerts and...
Source: www.keycdn.com

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

PyTorch might be a bit more popular than NewRelic. We know about 133 links to it since March 2021 and only 101 links to NewRelic. 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.

NewRelic mentions (101)

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 / 13 days 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 / 26 days 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 / about 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 / 3 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 / 3 months ago
View more

What are some alternatives?

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

Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.

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.

Zabbix - Track, record, alert and visualize performance and availability of IT resources

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

Dynatrace - Cloud-based quality testing, performance monitoring and analytics for mobile apps and websites. Get started with Keynote today!

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

Loading...