Software Alternatives, Accelerators & Startups

Scikit-learn VS NewRelic

Compare Scikit-learn VS NewRelic and see what are their differences

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Scikit-learn logo Scikit-learn

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

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.
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • NewRelic Landing page
    Landing page //
    2023-10-05

Scikit-learn features and specs

  • Ease of Use
    Scikit-learn provides a high-level interface for common machine learning algorithms, making it easy for beginners and professionals to implement complex models with minimal coding.
  • Extensive Documentation and Community Support
    The library has comprehensive documentation and a large, active community. This makes it easy to find tutorials, examples, and solutions to common problems.
  • Integration with Other Libraries
    Scikit-learn integrates well with other scientific computing libraries such as NumPy, SciPy, and pandas, allowing for seamless data manipulation and analysis.
  • Variety of Algorithms
    It offers a wide array of machine learning algorithms for tasks such as classification, regression, clustering, and dimensionality reduction.
  • Performance
    Designed with performance in mind, many of the algorithms are optimized and some even support multicore processing.

Possible disadvantages of Scikit-learn

  • Limited Deep Learning Support
    Scikit-learn is primarily focused on traditional machine learning algorithms and does not offer support for deep learning models, unlike libraries like TensorFlow or PyTorch.
  • Not Ideal for Large-Scale Data
    While Scikit-learn performs well for moderate-sized datasets, it may not be the best choice for extremely large datasets or big data applications.
  • Lack of Online Learning Algorithms
    The library has limited support for online learning algorithms, which are useful for scenarios where data arrives in a stream and model needs to be updated incrementally.
  • Less Flexibility in Customization
    It can be less flexible compared to lower-level libraries when highly customized or specific implementations are needed.
  • Dependency Overhead
    Scikit-learn relies on several other Python libraries like NumPy and SciPy, which might require users to manage multiple dependencies.

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.

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

NewRelic videos

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Category Popularity

0-100% (relative to Scikit-learn and NewRelic)
Data Science And Machine Learning
Monitoring Tools
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Performance Monitoring
0 0%
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 Scikit-learn and NewRelic

Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...

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.
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 should be more popular than Scikit-learn. It has been mentiond 100 times since March 2021. 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.

Scikit-learn mentions (31)

  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
  • 🚀 Launching a High-Performance DistilBERT-Based Sentiment Analysis Model for Steam Reviews 🎮🤖
    Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 5 months ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 11 months ago
  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / about 1 year ago
  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / almost 2 years ago
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NewRelic mentions (100)

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What are some alternatives?

When comparing Scikit-learn and NewRelic, you can also consider the following products

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

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.

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

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

NumPy - NumPy is the fundamental package for scientific computing with Python

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