Software Alternatives, Accelerators & Startups

Cypress.io VS Google BigQuery

Compare Cypress.io VS Google BigQuery and see what are their differences

Cypress.io logo Cypress.io

Slow, difficult and unreliable testing for anything that runs in a browser. Install Cypress in seconds and take the pain out of front-end testing.

Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.
  • Cypress.io Landing page
    Landing page //
    2023-04-17
  • Google BigQuery Landing page
    Landing page //
    2023-10-03

Cypress.io videos

Introduction to automation testing with Cypress.io (Non-selenium framework)

More videos:

  • Review - Testing Angular with Cypress.io | Joe Eames | AngularConnect 2018

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

Category Popularity

0-100% (relative to Cypress.io and Google BigQuery)
Automated Testing
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Browser Testing
100 100%
0% 0
Big Data
0 0%
100% 100

User comments

Share your experience with using Cypress.io and Google BigQuery. 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 Cypress.io and Google BigQuery

Cypress.io Reviews

20 Best JavaScript Frameworks For 2023
Cypress is a holistic automation testing framework where the tester can perform unit, integration, end-to-end, and regression testing. Additionally, they may orchestrate and unify outcomes with quality measurements and useful insights that support the agile workplace by leveraging the Cypress cloud.
Top 10 Perfecto alternatives with Zebrunner on top
- is a SaaS web app for easy scaling test runs and debugging failed tests. Pairs with the open source Cypress Test Runner.
Source: zebrunner.com

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.

Social recommendations and mentions

Google BigQuery might be a bit more popular than Cypress.io. We know about 35 links to it since March 2021 and only 26 links to Cypress.io. 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.

Cypress.io mentions (26)

  • Simulating Internet Outage and Recovery using Cypress
    In this blog post, we'll explore a Cypress test that replicates this scenario, utilizing the powerful intercept command to manipulate network requests and responses. - Source: dev.to / 5 months ago
  • Scraping a site?
    Maybe something like Cypress is what you're looking for? Cypress.io. Source: about 1 year ago
  • How to write tests in Django for JavaScript fetch
    You won't be able to test the javascript function itself from within python, but you can exercise the front-end code using something like cypress (https://cypress.io) or the older but still respectable selenium (https://selenium.dev). Source: over 1 year ago
  • What's your CI/CD flow made of?
    How are they run (services (ie. GitHub Action Runners, SauceLabs, Cypress.io, etc.), or self hosted autoscaling infrastructures)? Source: over 1 year ago
  • React, Vite and TypeScript: Get started in under 2 minutes
    You might have noticed the e2e folder. That's a fully-functioning setup of Cypress for doing integration-level or even full end-to-end tests. - Source: dev.to / over 1 year ago
View more

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
View more

What are some alternatives?

When comparing Cypress.io and Google BigQuery, you can also consider the following products

Selenium - Selenium automates browsers. That's it! What you do with that power is entirely up to you. Primarily, it is for automating web applications for testing purposes, but is certainly not limited to just that.

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

Robot framework - Robot Framework is a generic test automation framework for acceptance testing and acceptance...

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.

puppeteer - Puppeteer is a Node library which provides a high-level API to control headless Chrome or Chromium...

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.