Software Alternatives, Accelerators & Startups

Pandas VS Snowflake

Compare Pandas VS Snowflake and see what are their differences

Pandas logo Pandas

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

Snowflake logo Snowflake

Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.
  • Pandas Landing page
    Landing page //
    2023-05-12
  • Snowflake Landing page
    Landing page //
    2022-12-29

Pandas videos

Ozzy Man Reviews: Pandas

More videos:

  • Review - Ozzy Man Reviews: PANDAS Part 2
  • Review - Trash Pandas Review with Sam Healey

Snowflake videos

Grand Seiko Spring Drive "Snowflake" SBGA211 Luxury Watch Review

More videos:

  • Review - BEST GRAND SEIKO? Snowflake SBGA211 Review
  • Review - Grand Seiko Snowflake SBGA211 - Review and Impressions

Category Popularity

0-100% (relative to Pandas and Snowflake)
Data Science And Machine Learning
Big Data
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Data Dashboard
60 60%
40% 40

User comments

Share your experience with using Pandas and Snowflake. 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 Pandas and Snowflake

Pandas Reviews

25 Python Frameworks to Master
Pandas is a powerful and flexible open-source library used to perform data analysis in Python. It provides high-performance data structures (i.e., the famous DataFrame) and data analysis tools that make it easy to work with structured data.
Source: kinsta.com
Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
When it comes to ETL, you can do almost anything with Pandas if you're willing to put in the time. Plus, pandas is extraordinarily easy to run. You can set up a simple script to load data from a Postgre table, transform and clean that data, and then write that data to another Postgre table.
Source: www.xplenty.com

Snowflake Reviews

Top 6 Cloud Data Warehouses in 2023
Snowflake accommodates data analysts of all levels since it does not use Python or R programming language. It is also well known for its secure and compressed storage for semi-structured data. Besides this, it allows you to spin multiple virtual warehouses based on your needs while parallelizing and isolating individual queries boosting their performance. You can interact...
Source: geekflare.com
Top 5 Cloud Data Warehouses in 2023
Snowflake is one of the most popular data warehousing solutions on the market and delivers an incredible experience across multiple public clouds. By using Snowflake, companies can pull data from various business intelligence tools to do reporting and analytics without any database administration, thus avoiding high overhead costs. Unlike other data warehousing services,...
Top 5 BigQuery Alternatives: A Challenge of Complexity
Plus, Snowflake doesn’t include data integrations, so teams will have to bolt on an ETL tool to pipe their data into the warehouse. Those third-party pipelines add extra cost and overhead in the form of setup and maintenance that some teams may not want to absorb.
Source: blog.panoply.io
Top Big Data Tools For 2021
This platform can be used for data warehousing, data science, data engineering, sharing, and application development. It enables you to easily secure your data and execute various analytic workloads. Snowflake also ensures a seamless experience when working with multiple public clouds.

Social recommendations and mentions

Based on our record, Pandas seems to be a lot more popular than Snowflake. While we know about 201 links to Pandas, we've tracked only 4 mentions of Snowflake. 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.

Pandas mentions (201)

  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Use statistical analysis tools and libraries (e.g., Pandas for tabular data) to calculate and visualize these characteristics. For image datasets, custom scripts to analyze object sizes or mask distributions can be useful. Tools like OpenCV can assist in analyzing image properties, while libraries like Pandas and NumPy are excellent for tabular and numerical analysis. To address class... - Source: dev.to / 3 days ago
  • Awesome List
    Pandas - A powerful data analysis and manipulation library for Python. Pandas Documentation - Official documentation. - Source: dev.to / 9 days ago
  • The ultimate guide to creating a secure Python package
    It's also possible for you to give a package an alias by using the as keyword. For instance, you could use the pandas package as pd like this:. - Source: dev.to / about 1 month ago
  • AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions
    Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / about 2 months ago
  • Pandas reset_index(): How To Reset Indexes in Pandas
    In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / about 2 months ago
View more

Snowflake mentions (4)

  • DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
    Snowflake, a data warehousing company founded by ex-Oracle and ex-VectorWise experts, responded with a blog post that critically reviewed Databricks' findings, reported different results for the same benchmark, and claimed comparable price/performance to Databricks. - Source: dev.to / about 2 years ago
  • Personal Support at Internet Scale
    Snowflake: Snowflake is fast, and works well as a product analytics database. - Source: dev.to / over 2 years ago
  • Less than 1TB of data what tools should I get better at?
    If you just go to snowflake.com you can sign up for a demo account for free for a month and I'm fairly certain you can get more than one of these accounts (I would recycle emails doing it all the time.) Once you have an account there's lots of docs and videos out there either using the Database via their UI or via python using their connector. They also have a pyspark connector but you might want to just learn... Source: over 2 years ago
  • *BOMATO*
    Early stage funding & VCs clearly demarcate between tech companies and tech enabled companies. But, once the PE comes into the picture at the scale of BlackStone, the border between doordash.com and snowflake.com starts to blur. The motivation is to make some bucks by going to IPO and they know how to get it done. Source: almost 3 years ago

What are some alternatives?

When comparing Pandas and Snowflake, you can also consider the following products

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

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

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

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

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

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.