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TensorFlow VS NewRelic

Compare TensorFlow VS NewRelic and see what are their differences

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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.

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.
  • TensorFlow Landing page
    Landing page //
    2023-06-19
  • NewRelic Landing page
    Landing page //
    2023-10-05

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.

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.

Analysis of NewRelic

Overall verdict

  • Overall, NewRelic is regarded as a reliable and feature-rich APM solution. Its intuitive user interface, robust monitoring capabilities, and scalability generally receive positive feedback from users. However, it is essential to consider pricing and specific needs, as some users find it expensive compared to other solutions.

Why this product is good

  • NewRelic is considered a good choice for application performance monitoring (APM) because it offers comprehensive monitoring capabilities, real-time insights, and detailed analytics. It supports a wide range of programming languages and platforms, and features like distributed tracing, error analytics, and infrastructure monitoring make it a versatile tool for ensuring application reliability and performance.

Recommended for

  • Development teams needing real-time application performance insights
  • Organizations looking to monitor complex distributed applications
  • Businesses that require comprehensive monitoring across different technology stacks
  • Teams focusing on optimizing application availability and performance

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)

NewRelic videos

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

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Category Popularity

0-100% (relative to TensorFlow and NewRelic)

TensorFlow

NewRelic

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Monitoring Tools
0 0%
Monitoring Tools
100% 100
AI
100 100%
AI
0% 0
Performance Monitoring
0 0%
Performance Monitoring
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 TensorFlow and NewRelic

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

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

Social recommendations and mentions

Based on our record, NewRelic seems to be a lot more popular than TensorFlow. While we know about 101 links to NewRelic, 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.

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
View more

NewRelic mentions (101)

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What are some alternatives?

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

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

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.

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

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

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

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

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