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Google BigQuery VS Conda

Compare Google BigQuery VS Conda and see what are their differences

Google BigQuery logo Google BigQuery

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

Conda logo Conda

Binary package manager with support for environments.
  • Google BigQuery Landing page
    Landing page //
    2023-10-03
Not present

Google BigQuery videos

Cloud Dataprep Tutorial - Getting Started 101

More videos:

  • Review - Advanced Data Cleanup Techniques using Cloud Dataprep (Cloud Next '19)
  • Demo - Google Cloud Dataprep Premium product demo

Conda videos

No Conda videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Google BigQuery and Conda)
Data Dashboard
100 100%
0% 0
Front End Package Manager
Big Data
100 100%
0% 0
Package Manager
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 Google BigQuery and Conda

Google BigQuery Reviews

Top 6 Cloud Data Warehouses in 2023
You can also use BigQuery’s columnar and ANSI SQL databases to analyze petabytes of data at a fast speed. Its capabilities extend enough to accommodate spatial analysis using SQL and BigQuery GIS. Also, you can quickly create and run machine learning (ML) models on semi or large-scale structured data using simple SQL and BigQuery ML. Also, enjoy a real-time interactive...
Source: geekflare.com
Top 5 Cloud Data Warehouses in 2023
Google BigQuery is an incredible platform for enterprises that want to run complex analytical queries or “heavy” queries that operate using a large set of data. This means it’s not ideal for running queries that are doing simple filtering or aggregation. So if your cloud data warehousing needs lightning-fast performance on a big set of data, Google BigQuery might be a great...
Top 5 BigQuery Alternatives: A Challenge of Complexity
BigQuery's emergence as an attractive analytics and data warehouse platform was a significant win, helping to drive a 45% increase in Google Cloud revenue in the last quarter. The company plans to maintain this momentum by focusing on a multi-cloud future where BigQuery advances the cause of democratized analytics.
Source: blog.panoply.io
16 Top Big Data Analytics Tools You Should Know About
Google BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is a Platform as a Service that supports querying using ANSI SQL. It also has built-in machine learning capabilities.

Conda Reviews

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Social recommendations and mentions

Google BigQuery might be a bit more popular than Conda. We know about 35 links to it since March 2021 and only 30 links to Conda. 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.

Google BigQuery mentions (35)

  • Swirl: An open-source search engine with LLMs and ChatGPT to provide all the answers you need 🌌
    Using the Galaxy UI, knowledge workers can systematically review the best results from all configured services including Apache Solr, ChatGPT, Elastic, OpenSearch, PostgreSQL, Google BigQuery, plus generic HTTP/GET/POST with configurations for premium services like Google's Programmable Search Engine, Miro and Northern Light Research. - Source: dev.to / 10 months ago
  • Modern data stack: scaling people and technology at FINN
    Data Transformations: This phase involves modifying and integrating tables to generate new tables optimized for analytical use. Consider this example: you want to understand the purchasing behavior of customers aged between 20-30 in your online shop. This means you'll need to join product, customer, and transaction data to create a unified table for analytics. These data preparation tasks (e.g., joining... - Source: dev.to / 10 months ago
  • Running Transformations on BigQuery using dbt Cloud: step by step
    Introduction In today's data-driven world, transforming raw data into valuable insights is crucial. This process, however, often involves complex tasks that demand efficiency, scalability, and reliability. Enter dbt Cloud—a powerful tool that simplifies data transformations on Google BigQuery. In this article, we'll take you through a step-by-step guide on how to run BigQuery transformations using dbt Cloud.... - Source: dev.to / 11 months ago
  • Do I need a cloud computing–based data cloud company
    You'll want to evaluate what BigQuery has to offer and see if it makes sense for you to move over. Source: about 1 year ago
  • I used ChatGPT to get an Internship
    Watch the introductory videos on BigQuery on the Google Cloud Platform website (https://cloud.google.com/bigquery). Source: about 1 year ago
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Conda mentions (30)

  • Python's virtual environments
    Conda is an open-source package management system and environment management system that runs on Windows, macOS, and Linux. It is a powerful tool that allows you to create and manage virtual environments, install and update packages, and manage dependencies. Conda is particularly popular in the scientific computing community, as it provides access to a wide range of scientific computing libraries and tools. I... - Source: dev.to / 2 days ago
  • Introducing Flama for Robust Machine Learning APIs
    When dealing with software development, reproducibility is key. This is why we encourage you to use Python virtual environments to set up an isolated environment for your project. Virtual environments allow the isolation of dependencies, which plays a crucial role to avoid breaking compatibility between different projects. We cannot cover all the details about virtual environments in this post, but we encourage... - Source: dev.to / 7 months ago
  • Ask HN: Package management for multiple modules in C++, Python, Java project?
    Conda https://docs.conda.io/en/latest/ ?? I'm not sure, but I used it to download some Python packages. It's an alternative to pip, but I'm not sure about the details. - Source: Hacker News / 7 months ago
  • How To Manage Environment For Data Science Project Using Conda
    Conda is an open-source package management and environment management system that can be used to create different isolated development environments. Conda can be used in place of pipenv to create a virtual environment. - Source: dev.to / about 1 year ago
  • Full system upgrade just killed all my python virtualenvs
    Congrats you discovered why Poetry and Conda projects exist! Source: about 1 year ago
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What are some alternatives?

When comparing Google BigQuery and Conda, you can also consider the following products

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

Homebrew - The missing package manager for macOS

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.

pkgsrc - pkgsrc is a framework for building over 17,000 open source software packages.

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.

Yay - Yay is an AUR helper written in go, based on the design of yaourt, apacman and pacaur.