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Meltano VS Matplotlib

Compare Meltano VS Matplotlib and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Meltano logo Meltano

Open source data dashboarding

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Meltano Landing page
    Landing page //
    2023-08-04
  • Matplotlib Landing page
    Landing page //
    2023-06-14

Meltano features and specs

  • Open Source
    Meltano is open-source, which means that it is free to use and can be customized according to specific business needs. The open-source nature fosters a community-driven approach to improvements and updates.
  • Modular Architecture
    Meltano offers a modular architecture that allows users to mix and match different components like extractors, loaders, and transformers, providing flexibility and adaptability.
  • Integration with Singer Taps
    It is compatible with Singer Taps and Targets, enabling Meltano to connect with a wide variety of data sources and destinations, making data integration seamless.
  • Command Line Interface (CLI)
    Meltano provides a robust CLI that simplifies managing and orchestrating ETL workflows, which can be advantageous for developers who prefer working with command-line tools.
  • Community and Support
    There is a vibrant community and an active support system, which can be helpful for troubleshooting and getting advice on best practices regarding Meltano usage.

Possible disadvantages of Meltano

  • Steep Learning Curve
    For users who are not familiar with command line tools or open-source data integration platforms, Meltano can have a steep learning curve, requiring time and effort to master.
  • Limited Built-in Features
    While being modular offers flexibility, Meltano has fewer built-in features compared to some commercial ETL tools, which might require users to build custom solutions.
  • Variable Support for Sources/Destinations
    The quality and reliability of connectors can vary since Meltano relies on community-contributed Singer Taps, which may not be as stable or well-documented as proprietary alternatives.
  • Complex Configuration
    Initial setup and configuration can be complex, especially when connecting to multiple data sources or when customization is necessary, which may require significant technical expertise.
  • Resource Dependency
    As an evolving open-source project, Meltano may require more resources in terms of time and effort to stay updated with the latest features and community contributions.

Matplotlib features and specs

  • Versatility
    Matplotlib can generate a wide variety of plots, ranging from simple line plots to complex 3D plots. This versatility makes it a go-to library for many scientific and technical visualizations.
  • Customization
    It offers extensive customization options for virtually every element of a plot, including colors, labels, line styles, and more, allowing users to tailor plots to meet specific needs.
  • Integrations
    Matplotlib integrates well with other Python libraries such as NumPy, Pandas, and SciPy, making it easier to plot data directly from these sources.
  • Community and Documentation
    It has a large, active community and comprehensive documentation that includes tutorials, examples, and detailed references, which can help users solve problems and improve their plot-making skills.
  • Interactivity
    Matplotlib supports interactive plots, which can be embedded in Jupyter notebooks and GUIs, allowing for dynamic data exploration and presentation.
  • Publication-Quality
    The library is capable of producing high-quality, publication-ready graphics that meet the stringent requirements of academic journals and professional presentations.

Possible disadvantages of Matplotlib

  • Complexity
    While Matplotlib offers extensive customization, it can be complex and sometimes unintuitive for beginners, requiring a steep learning curve to master all its functionality.
  • Performance
    Rendering a large number of plots or handling very large datasets can be slow, making Matplotlib less suitable for real-time data visualization.
  • Modern Aesthetics
    Out-of-the-box plots from Matplotlib can look somewhat dated compared to those from newer plotting libraries like Seaborn or Plotly, requiring additional customization to achieve a modern look.
  • 3D Plots
    Although Matplotlib supports 3D plotting, its capabilities are relatively limited and less sophisticated compared to specialized 3D plotting libraries.
  • Size and Structure
    The package is relatively large and can be slow to import. Its extensive structure can make finding specific functions and understanding the overall architecture challenging.

Analysis of Matplotlib

Overall verdict

  • Yes, Matplotlib is a good library for data visualization, particularly for users who require a versatile and powerful plotting solution in Python.

Why this product is good

  • Matplotlib is highly regarded due to its extensive customization options, versatility in creating a wide range of static, animated, and interactive plots, and its large user community and support. It integrates well with other scientific libraries in Python, making it a staple for data visualization. The library is also open-source and frequently updated, ensuring it remains a reliable choice for users.

Recommended for

  • Data scientists and analysts needing to create detailed, customized visual representations of their data.
  • Researchers and engineers looking for a comprehensive plotting library that supports scientific and engineering formats.
  • Python developers who require integration with other scientific computing libraries like NumPy and Pandas.

Meltano videos

+ Add

Meltano tutorial

More videos:

  • Demo - Meltano Sprint Review & Demo Day 2019-11-08
  • Review - Meltano Weekly Sprint Review 2019-11-01

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Meltano and Matplotlib)

Meltano

Matplotlib

Developer Tools
100 100%
Developer Tools
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Data Dashboard
35 35%
Data Dashboard
65% 65
Technical Computing
0 0%
Technical Computing
100% 100

User comments

Share your experience with using Meltano and Matplotlib. For example, how are they different and which one is better?
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Reviews

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

Meltano Reviews

Top 11 Fivetran Alternatives for 2024
Meltano was established in 2018 as an open-source project within GitLab to assist their data and analytics team. Itโ€™s a Python framework based on the Singer protocol. Originally developed by the founders of Stitch, the Singer framework saw reduced contributions after Stitch was acquired by Talend, which was later acquired by Qlik. Despite these changes, Meltano has continued...
Source: estuary.dev
Top 10 Fivetran Alternatives - Listing the best ETL tools
The platform provides users with a wide range of integration options, including connectors for databases, APIs, and application logs. Additionally, Meltano provides extensive support for data transformation and orchestration and integrates well with several cloud-based data warehouses.
Source: weld.app

Matplotlib Reviews

25 Python Frameworks to Master
Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.
Source: kinsta.com
5 Best Python Libraries For Data Visualization in 2023
You can use this library for multiple purposes such as generating plots, bar charts, histograms, power spectra, stemplots, pie charts, and more. The best thing about Matplotlib is you just have to write a few lines of code and it handles the rest by itself. Metaplotilib focuses on static images for publication along with interactive figures using toolkits like Qt and GTK.
Source: www.technotification.com
15 data science tools to consider using in 2021
Matplotlib is an open source Python plotting library that's used to read, import and visualize data in analytics applications. Data scientists and other users can create static, animated and interactive data visualizations with Matplotlib, using it in Python scripts, the Python and IPython shells, Jupyter Notebook, web application servers and various GUI toolkits.
Source: searchbusinessanalytics.techtarget.com
Top Python Libraries For Image Processing In 2021
Matplotlib is primarily used for 2D visualizations such as scatter plots, bar graphs, histograms, and many more, but we can also use it for image processing. It is effective to get information out of an image. It doesnโ€™t support all file formats.
Source: www.analyticsvidhya.com
Top 8 Python Libraries for Data Visualization
Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community. It comes with an interactive environment across multiple platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application...
Source: www.geeksforgeeks.org

Social recommendations and mentions

Based on our record, Matplotlib should be more popular than Meltano. It has been mentiond 114 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.

Meltano mentions (26)

  • AI product development is being held back by data engineering
    Hey HN, Arch CEO here! Our team has been working at the intersection of data engineering and software engineering for a few years now with Meltano (https://meltano.com), and this year, the rise in Generative AI has made it clear that the bottleneck in unlocking the potential value of data has shifted from data integration on data teams to data engineering on software teams, so weโ€™ve decided to do something about... - Source: Hacker News / almost 3 years ago
  • How useful is Airbytes in production pipelines?
    We use Meltano for (EL) and Prefect for scheduling. Is not click-ops, but works very well for us! Behind the scenes Meltano wraps up Singer spec similarly like Airbyte does with its connectors. Before that we tried Airbyte (~5 months ago?) and it was so bad.. We could not choose the columns to replicate and the connectors were unstable i.e. Skipping data, all sort of odd errors and so on.. Source: about 3 years ago
  • Ask HN: Who is hiring? (May 2023)
    Meltano's all-remote team and community of thousands are on a mission to enable everyone to realize the full potential of their data. To this end, we are bringing software engineering best practices to data teams in the form of an open-source DataOps platform that we envision becoming the foundation of every team's ideal data stack. Our public company handbook (https://handbook.meltano.com/) has all the details on... - Source: Hacker News / over 3 years ago
  • Ask HN: Who is hiring? (April 2023)
    Meltano | Full-Time | Remote | https://meltano.com Meltano's all-remote team and community of thousands are on a mission to enable everyone to realize the full potential of their data. To this end, we are bringing software engineering best practices to data teams in the form of an open-source DataOps platform that we envision becoming the foundation of every team's ideal data stack. Our public company handbook... - Source: Hacker News / over 3 years ago
  • If dbt is the "T" part of an "ELT", what do you use for "EL"?
    We switched from AWS Glue to Meltano for the EL part of ELT and it's been a joy to use. We're moving so much faster now. Source: over 3 years ago
View more

Matplotlib mentions (114)

  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ€” the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 5 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes itโ€™s easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 8 months ago
  • libmalloc, jemalloc, tcmalloc, mimalloc - Exploring Different Memory Allocators
    We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 9 months ago
  • Building an AI Scoring Agent: Step-By-Step
    NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 10 months ago
  • Top 5 GitHub Repositories for Data Science in 2026
    The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโ€ฆ. - Source: dev.to / 11 months ago
View more

What are some alternatives?

When comparing Meltano and Matplotlib, you can also consider the following products

Airbyte - Replicate data in minutes with prebuilt & custom connectors

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

Fivetran - Fivetran offers companies a data connector for extracting data from many different cloud and database sources.

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

Apache Superset - modern, enterprise-ready business intelligence web application

Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.

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