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RAWGraphs VS Apache Storm

Compare RAWGraphs VS Apache Storm and see what are their differences

RAWGraphs logo RAWGraphs

RAWGraphs is an open source app built with the goal of making the visualization of complex data...

Apache Storm logo Apache Storm

Apache Storm is a free and open source distributed realtime computation system.
  • RAWGraphs Landing page
    Landing page //
    2022-06-16
  • Apache Storm Landing page
    Landing page //
    2019-03-11

RAWGraphs features and specs

  • User-Friendly Interface
    RAWGraphs provides an intuitive drag and drop interface, making it accessible for users with various technical skills.
  • Open Source
    Being open source, RAWGraphs allows for customization and community contributions, promoting transparency and flexibility.
  • Supports Multiple Data Formats
    RAWGraphs supports a variety of input formats like CSV, TSV, JSON, etc., enhancing its adaptability to different data sources.
  • Extensive Visualization Types
    Offers a wide range of visualization types such as bar graphs, scatter plots, and network graphs, catering to diverse analytical needs.
  • No Installation Required
    As a web-based tool, it does not require any installation, making it easy to access and use anywhere with an internet connection.
  • Export Options
    Allows exporting visualizations in vector (SVG) and raster (PNG) formats, which is valuable for high-quality reporting and presentations.

Possible disadvantages of RAWGraphs

  • Limited Interactivity
    Visualizations created with RAWGraphs are generally static, lacking advanced interactive features found in other tools.
  • Performance with Large Datasets
    May struggle with performance issues when handling very large datasets, which can limit its use for extensive data analytics.
  • Learning Curve for Advanced Features
    While basic functionalities are user-friendly, leveraging advanced features and customizations may require a steeper learning curve.
  • Dependency on Internet
    As a web-based application, it requires an internet connection to function, which can be a limitation in restricted or offline environments.
  • Limited Data Manipulation
    Provides basic data manipulation features, but lacks the depth and complexity available in specialized data processing tools.
  • Support and Documentation
    As an open-source project, it may not have the extensive support and documentation available with commercial visualization tools.

Apache Storm features and specs

  • Real-Time Processing
    Apache Storm is designed for processing data in real-time, which makes it ideal for applications like fraud detection, recommendation systems, and monitoring tools.
  • Scalability
    Storm is capable of scaling horizontally, allowing it to handle increasing amounts of data by adding more nodes, making it suitable for large-scale applications.
  • Fault Tolerance
    Storm provides robust fault-tolerance mechanisms by rerouting tasks from failed nodes to operational ones, ensuring continuous processing.
  • Broad Language Support
    Apache Storm supports multiple programming languages, including Java, Python, and Ruby, allowing developers to use the language they are most comfortable with.
  • Open Source Community
    Being an Apache project, Storm benefits from a strong open-source community, which contributes to its development and offers abundant resources and support.

Possible disadvantages of Apache Storm

  • Complex Setup
    Setting up and configuring Apache Storm can be complex and time-consuming, requiring detailed knowledge of its architecture and the underlying infrastructure.
  • High Learning Curve
    The architecture and components of Storm can be difficult for new users to grasp, leading to a steeper learning curve compared to some other streaming platforms.
  • Maintenance Overhead
    Managing and maintaining a Storm cluster can require significant effort, including monitoring, troubleshooting, and scaling the infrastructure.
  • Error Handling
    While Storm is fault-tolerant, its error handling at the application level can sometimes be challenging, requiring careful design to manage failures effectively.
  • Resource Intensive
    Storm can be resource-intensive, particularly in terms of memory and CPU usage, which can lead to increased costs and necessitate powerful hardware.

Analysis of RAWGraphs

Overall verdict

  • Yes, RAWGraphs is a good tool for creating data visualizations due to its ease of use, versatility, and robust support for different data types and outputs.

Why this product is good

  • RAWGraphs is considered a good data visualization tool because it is open-source, versatile, and easy to use. It allows users to create a wide variety of charts and visualizations without needing extensive coding knowledge. Its interface is intuitive and facilitates the quick transformation of data sets into visually compelling graphics. Furthermore, it supports multiple formats for data input and export, making it flexible for various project needs.

Recommended for

  • data analysts
  • journalists
  • researchers
  • educators
  • students
  • designers who need to create visualizations without in-depth coding skills.

RAWGraphs videos

RawGraphs Walkthrough

Apache Storm videos

Apache Storm Tutorial For Beginners | Apache Storm Training | Apache Storm Example | Edureka

More videos:

  • Review - Developing Java Streaming Applications with Apache Storm
  • Review - Atom Text Editor Option - Real-Time Analytics with Apache Storm

Category Popularity

0-100% (relative to RAWGraphs and Apache Storm)
Data Visualization
100 100%
0% 0
Big Data
0 0%
100% 100
Charting Libraries
100 100%
0% 0
Stream Processing
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 RAWGraphs and Apache Storm

RAWGraphs Reviews

Top 10 Tableau Open Source Alternatives: A Comprehensive List
RAWGraphs is an open-source Data Visualization tool designed to make visualizing complex data simple for everyone. The primary goal of RAWGraphs is to provide a tool that allows people who do not have the technical/coding expertise to create visualizations on their own. Originally designed to help graphic designers complete a set of tasks that were not available in other...
Source: hevodata.com

Apache Storm Reviews

Top 15 Kafka Alternatives Popular In 2021
Apache Storm is a recognized, distributed, open-source real-time computational system. It is free, simple to use, and helps in easily and accurately processing multiple data streams in real-time. Because of its simplicity, it can be utilized with any programming language and that is one reason it is a developerโ€™s preferred choice. It is fast, scalable, and integrates well...
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Storm is an open-source distributed real-time computational system for processing data streams. Similar to what Hadoop does for batch processing, Apache Storm does for unbounded streams of data in a reliable manner. Built by Twitter, Apache Storm specifically aims at the transformation of data streams. Storm has many use cases like real-time analytics, online machine...

Social recommendations and mentions

Based on our record, Apache Storm should be more popular than RAWGraphs. It has been mentiond 11 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.

RAWGraphs mentions (5)

  • Interview synthesis tools?
    Go back through a second time Code themes / pull insights/ double check for keywords tag accuracy Use Dovetailโ€™s โ€œchartsโ€ to review various tags (it will show you how many tags per word in various chart options, none are great.) Export desired csvโ€™s from Dovetail Charts to free online data viz software like https://rawgraphs.io Boom. Iโ€™m sure there are better ways but thatโ€™s what I got! Source: over 4 years ago
  • What type/style of chart is this?
    Sankey is probably the most common name (after Captain Matthew Henry Phineas Riall Sankey who apparently made them to study energy flows in steam engines). But I've also heard it referred to as an alluvial diagram, for example in https://rawgraphs.io/. Source: over 4 years ago
  • Show HN: I made a data visualization desktop app
    This seems quite similar to RawGraphs: https://rawgraphs.io/ Both seem to provide a similar interface for dragging in a CSV file and constructing a chart, but RawGraphs is open-source, and can be used in the browser without installing anything (or the code can be downloaded and served locally). The main advantage of Daigo over RawGraphs seems to be that it supports publishing multiple charts as a dashboard.... - Source: Hacker News / over 4 years ago
  • [OC] Latin Americaโ€™s biggest airports had been growing steadily. With Covid, it all changed.
    Tools: Excel, Rawgraphs, Affinity Designer. Source: over 4 years ago
  • Self-hosted solution for easy data visualization?
    Take a look at https://rawgraphs.io/. Source: about 5 years ago

Apache Storm mentions (11)

  • Data Engineering and DataOps: A Beginner's Guide to Building Data Solutions and Solving Real-World Challenges
    There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 3 years ago
  • Real Time Data Infra Stack
    Although this article lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem. - Source: dev.to / over 3 years ago
  • In One Minute : Hadoop
    Storm, a system for real-time and stream processing. - Source: dev.to / over 3 years ago
  • Elon Musk reportedly wants to fire 75% of Twitterโ€™s employees
    Google has scaled well and has helped others scale, Twitter has always been behind by years. I think the only thing they did well was Twitter Storm, now taken up by Apache Foundation. Source: almost 4 years ago
  • Spark for beginners - and you
    Streaming: Sparks Streamings's latency is at least 500ms, since it operates on micro-batches of records, instead of processing one record at a time. Native streaming tools like Storm, Apex or Flink might be better for low-latency applications. - Source: dev.to / over 4 years ago
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What are some alternatives?

When comparing RAWGraphs and Apache Storm, you can also consider the following products

Plotly - Low-Code Data Apps

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.