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Panoply VS Jupyter

Compare Panoply VS Jupyter and see what are their differences

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Panoply logo Panoply

Panoply is a smart cloud data warehouse

Jupyter logo Jupyter

Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
  • Panoply Landing page
    Landing page //
    2023-09-27

Panoply is a smart data warehouse that automates all three key aspects of the data analytics stack: data collection & transformation (ETL), database storage management, and query performance optimization. Panoply empowers anyone working with data analytics to quickly gain actionable insights on their own - without the need of IT and Engineering.

  • Jupyter Landing page
    Landing page //
    2023-06-22

Panoply

Categories
  • Data Management
  • Data Warehousing
  • ETL
  • Data Integration
  • Business Intelligence
  • Data Analytics
  • Database Tools
Website panoply.io
Pricing URL Official Panoply Pricing
Details $paid Free Trial $200.0 / Monthly
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Jupyter

Categories
  • Data Science And Machine Learning
  • Data Science Tools
  • Data Science Notebooks
  • Data Science IDE
  • Data Analysis
Website jupyter.org
Pricing URL-
Details $-
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Panoply videos

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Panoply demo: Get faster data analytics in minutes!

Jupyter videos

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What is Jupyter Notebook?

More videos:

  • Tutorial - Jupyter Notebook Tutorial: Introduction, Setup, and Walkthrough
  • Review - JupyterLab: The Next Generation Jupyter Web Interface

Category Popularity

0-100% (relative to Panoply and Jupyter)

Panoply

Jupyter

Data Management
100 100%
Data Management
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Data Integration
100 100%
Data Integration
0% 0
Data Dashboard
0 0%
Data Dashboard
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 Panoply and Jupyter

Panoply Reviews

Top 14 ETL Tools for 2023
Panoply is an automated, self-service cloud data warehouse that aims to simplify the data integration process. Any data connector with a standard ODBC/JDBC connection, Postgres connection, or AWS Redshift connection is compatible with Panoply. In addition, users can connect Panoply with other ETL tools, such as Stitch and Fivetran, to further augment their data integration...
Source: www.integrate.io
Top 5 BigQuery Alternatives: A Challenge of Complexity
Although Panoply was developed for data analysts, you don't have to be one to use it. Anyone with a good understanding of SQL can get a data pipeline up and running within a matter of minutes. This frees up your time to focus on analysis, whether you’re running queries directly in Panoply or in your favorite BI tool.
Source: blog.panoply.io
Top ETL Tools For 2021...And The Case For Saying "No" To ETL
Under the hood, Panoply uses a flexible ELT approach (rather than traditional ETL), which makes data ingestion much faster and more dynamic, since you don’t have to wait for transformation to complete before loading your data. And since Panoply builds managed cloud data warehouses for every user, you won’t need to set up a separate destination to store all the data you pull...
Source: blog.panoply.io
Top 7 ETL Tools for 2021
Panoply is an automated, self-service cloud data warehouse that aims to simplify the data integration process. Any data connector with a standard ODBC/JDBC connection, Postgres connection, or AWS Redshift connection is compatible with Panoply. In addition, users can connect Panoply with other ETL tools such as Stitch and Fivetran to further augment their data integration...
Source: www.xplenty.com

Jupyter Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Once you install nteract, you can open your notebook without having to launch the Jupyter Notebook or visit the Jupyter Lab. The nteract environment is similar to Jupyter Notebook but with more control and the possibility of extension via libraries like Papermill (notebook parameterization), Scrapbook (saving your notebook’s data and photos), and Bookstore (versioning).
Source: lakefs.io
7 best Colab alternatives in 2023
JupyterLab is the next-generation user interface for Project Jupyter. Like Colab, it's an interactive development environment for working with notebooks, code, and data. However, JupyterLab offers more flexibility as it can be self-hosted, enabling users to use their own hardware resources. It also supports extensions for integrating other services, making it a highly...
Source: deepnote.com
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
Jupyter Notebook is a widely popular tool for data scientists to work on data science projects. This article reviews the top 12 alternatives to Jupyter Notebook that offer additional features and capabilities.
Source: noteable.io
15 data science tools to consider using in 2021
Jupyter Notebook's roots are in the programming language Python -- it originally was part of the IPython interactive toolkit open source project before being split off in 2014. The loose combination of Julia, Python and R gave Jupyter its name; along with supporting those three languages, Jupyter has modular kernels for dozens of others.
Source: searchbusinessanalytics.techtarget.com
Top 4 Python and Data Science IDEs for 2021 and Beyond
Yep — it’s the most popular IDE among data scientists. Jupyter Notebooks made interactivity a thing, and Jupyter Lab took the user experience to the next level. It’s a minimalistic IDE that does the essentials out of the box and provides options and hacks for more advanced use.
Source: towardsdatascience.com

Social recommendations and mentions

Based on our record, Jupyter seems to be a lot more popular than Panoply. While we know about 203 links to Jupyter, we've tracked only 3 mentions of Panoply. 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.

Panoply mentions (3)

Jupyter mentions (203)

  • Scrape Redfin Property Data
    Choosing IDE: Selecting a suitable Integrated Development Environment (IDE) is crucial for efficient coding. Consider popular options such as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and ensure it's configured to work with Python. - Source: dev.to / about 4 hours ago
  • Groovy 🎷 Cheat Sheet - 01 Say "Hello" from Groovy
    Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / about 2 months ago
  • Using IPython Jupyter Magic commands to improve the notebook experience
    Note. Nowadays, there are many flavors of notebooks (Jupyter, VSCode, Databricks, etc.), but they’re all built on top of IPython. Therefore, the Magics developed should be reusable across environments. - Source: dev.to / about 2 months ago
  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    They make it easy to launch multiple case-by-case data science projects and run your local code right from Jupyter Notebook. - Source: dev.to / 2 months ago
  • MLOps in practice: building and deploying a machine learning app
    Talking to some colleagues and friends lately gathering some ideas of a nice Machine Learning project to build, I’ve seen that there’s a gap of knowledge in terms of how do one exactly uses a Machine Learning model trained? Just imagine yourself building a model to solve some problem, you are probably using Jupyter Notebook to perform some data clean up, perform some normalization and further tests. Then you... - Source: dev.to / 3 months ago
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What are some alternatives?

When comparing Panoply and Jupyter, you can also consider the following products

Supermetrics - Supermetrics condenses all the major vectors of data relevant to a user's marketing campaigns and helps them make sense of it all.

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

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

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

QuickBI - Export data from over 300 sources to a data warehouse and analyze it with a reporting tool of your choice. Quick and easy setup.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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