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Graphite VS Papers with Code

Compare Graphite VS Papers with Code and see what are their differences

Graphite logo Graphite

Graphite is a highly scalable real-time graphing system.

Papers with Code logo Papers with Code

The latest in machine learning at your fingerprints
  • Graphite Landing page
    Landing page //
    2021-10-13
  • Papers with Code Landing page
    Landing page //
    2022-07-17

Graphite features and specs

  • Scalability
    Graphite is designed for high performance and can handle large volumes of time-series data, making it suitable for scaling up as data grows.
  • Flexibility
    Graphite offers a flexible schema, allowing users to define their own metrics and naming conventions that best suit their monitoring needs.
  • Integration
    Graphite integrates easily with a variety of data sources and visualization tools such as Grafana, making it a versatile option for many monitoring setups.
  • Open Source
    Being an open-source tool, Graphite has a strong community for support and contributions, and it is also free to use without licensing costs.
  • Customizability
    Graphite allows for extensive customization of dashboards and visualization options, providing users with many ways to view and interpret their data.

Possible disadvantages of Graphite

  • Complex Setup
    The initial setup and configuration of Graphite can be complex and time-consuming, often requiring in-depth knowledge of the system.
  • Performance Issues
    While Graphite is designed for high performance, it can sometimes struggle with write-heavy loads and may require additional setup to maintain efficiency.
  • High Resource Consumption
    Graphite can consume significant system resources, especially disk I/O and CPU, which might be a concern for environments with limited resources.
  • Limited Built-in Visualization
    The native Graphite-web UI is considered less feature-rich compared to more modern tools like Grafana, which may necessitate additional tools for better visualization.
  • Maintenance Overhead
    Due to its complexity and resource needs, maintaining Graphite can involve a significant overhead, particularly in larger or more dynamic environments.

Papers with Code features and specs

  • Open Access
    Papers with Code provides free access to a vast repository of research papers and code implementations, making cutting-edge research available to a wider audience.
  • Reproducibility
    By linking research papers with their corresponding code, it promotes reproducibility, allowing researchers to verify results and build upon previous work more effectively.
  • Benchmarking
    The platform offers benchmarking tools and leaderboards, facilitating the comparison of different models and approaches on standard datasets and fostering competition in the research community.
  • Community Engagement
    Researchers and developers can contribute their own code and evaluations, which encourages community collaboration and the sharing of knowledge.
  • Resource Saving
    By providing implementations and datasets, it saves researchers time and resources, enabling them to focus on innovation rather than recreating existing work.

Possible disadvantages of Papers with Code

  • Quality Control
    Not all code implementations are thoroughly vetted or peer-reviewed, which can lead to issues with code quality and reliability.
  • Misalignment of Benchmarks
    Benchmarks and evaluations might not perfectly align with certain niche or novel research tasks, potentially skewing perceptions about model performance.
  • Dependence on Contributor Participation
    The platform relies heavily on community contributions; if participation wanes, the updates and breadth of resources could stagnate.
  • Integration Challenges
    Integrating and adapting third-party code into different environments or existing projects can sometimes be challenging due to dependencies or compatibility issues.
  • Information Overload
    With a vast amount of available papers and code, navigating and finding the most relevant and high-quality resources can be overwhelming for users.

Analysis of Graphite

Overall verdict

  • Graphite (graphiteapp.org) is generally considered a good tool for real-time graphing of time-series data.

Why this product is good

  • Graphite is appreciated for its powerful and flexible graphing capabilities, scalability, and open-source nature. It's widely used for monitoring and visualization due to its robust ecosystem and the ability to handle large amounts of data efficiently.

Recommended for

    Graphite is recommended for developers, system administrators, and IT professionals who need to monitor and visualize time-series data, particularly those working in environments with large-scale data monitoring needs.

Graphite videos

Review: Samson Graphite 49 & Graphite 25 | Audio Mentor

More videos:

  • Demo - Faber-Castell 9000 graphite pencil review and tiger demo - w/ Lachri
  • Review - Graphite pencil brand review

Papers with Code videos

The best site for research papers with codes on Machine/Deep Learning | Research paper search

More videos:

  • Review - Papers With Code Machine Learning Papers and Code Free Resource

Category Popularity

0-100% (relative to Graphite and Papers with Code)
Developer Tools
77 77%
23% 23
AI
46 46%
54% 54
Monitoring Tools
100 100%
0% 0
Data Science And Machine Learning

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Graphite and Papers with Code

Graphite Reviews

The 10 Best Nagios Alternatives in 2024 (Paid and Open-source)
Although Graphite's UI might not be the most impressive, it seamlessly integrates with Grafana for improved visualizations. It's important to note that Graphite itself doesn't collect data directly; instead, applications need to be configured to send data to Graphite. Carbon then listens for this data and forwards it to Whisper, where it is stored in time series format on...
Source: betterstack.com
4 Best Time Series Databases To Watch in 2019
Graphite is a even more established and very widely used time series database system. Graphite is a powerful monitoring tool that store numeric time series data and display them on demand via its Graphite-web interface at a fair speed. Graphite is most of the time used as a system, network and application performance metric store. Big companies such as Booking.com, Reddit...
Source: medium.com

Papers with Code Reviews

We have no reviews of Papers with Code yet.
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Social recommendations and mentions

Based on our record, Papers with Code should be more popular than Graphite. 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.

Graphite mentions (16)

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Papers with Code mentions (100)

  • What does HumaneBench AI benchmark reveal about chatbot safety?
    Benchmark Primary focus Evaluation metrics System coverage Usability Link HumaneBench AI benchmark Human well being, humane AI principles HumaneScore, flip tests under adversarial instruction, long term well being 15 popular chat models tested across 800 realistic scenarios Designed for chatbot safety research; requires ensemble judging for... - Source: dev.to / 8 months ago
  • Computer Vision Made Simple with ReductStore and Roboflow
    An helpful approach is to browse the state of the art models in paperswithcode. This will give you an idea of the performance of different models on various tasks. - Source: dev.to / almost 2 years ago
  • Show HN: Simple Science โ€“ The Newest Science Explained Simply
    I think a way around this would some sort of voting/ popularity system? Papers with code (https://paperswithcode.com/) does this via Github stars sorting. Sure it doesn't mean something is established. But it at least gives some way to filter through the firehose of papers. Love this project btw! I think it has potential (and the timing is right now that everyone is looking for the next "attention is all... - Source: Hacker News / almost 2 years ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    Adapting to Evolving Standards: With the rapid progress in deep learning research and applications, staying current with the latest developments is crucial. The checklist underscores the importance of considering established standard architectures and leveraging current state-of-the-art (SOTA) resources, like paperswithcode.com, to guide project decisions. This dynamic approach ensures that projects benefit from... - Source: dev.to / about 2 years ago
  • Understanding Technical Research Papers
    Papers With Code is one of the good resources to get you to get started. - Source: dev.to / about 2 years ago
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What are some alternatives?

When comparing Graphite and Papers with Code, you can also consider the following products

CodeRabbit - Unleash AI on Your Code Reviews with CodeRabbit

ML5.js - Friendly machine learning for the web

GitHub - Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.

arXiv - arXiv is a free distribution service and an open-access archive for scholarly articles.

Prometheus - An open-source systems monitoring and alerting toolkit.

Spell - Deep Learning and AI accessible to everyone