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NewRelic VS NumPy

Compare NewRelic VS NumPy and see what are their differences

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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.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • NewRelic Landing page
    Landing page //
    2023-10-05
  • NumPy Landing page
    Landing page //
    2023-05-13

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.

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

NewRelic videos

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NumPy videos

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Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Category Popularity

0-100% (relative to NewRelic and NumPy)

NewRelic

NumPy

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

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Reviews

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

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

NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Social recommendations and mentions

NumPy might be a bit more popular than NewRelic. We know about 119 links to it since March 2021 and only 100 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 (100)

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NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 4 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 8 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 8 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 9 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 9 months ago
View more

What are some alternatives?

When comparing NewRelic and NumPy, 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.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

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!

OpenCV - OpenCV is the world's biggest computer vision library

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