Software Alternatives, Accelerators & Startups

Google App Engine VS Google BigQuery

Compare Google App Engine VS Google BigQuery and see what are their differences

Google App Engine logo Google App Engine

A powerful platform to build web and mobile apps that scale automatically.

Google BigQuery logo Google BigQuery

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

Google App Engine videos

Get to know Google App Engine

More videos:

  • Review - Developing apps that scale automatically with Google App Engine

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 Google App Engine and Google BigQuery)
Cloud Computing
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Cloud Hosting
100 100%
0% 0
Big Data
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 App Engine and Google BigQuery

Google App Engine Reviews

Top 5 Alternatives to Heroku
Google App Engine is fast, easy, but not that very cheap. The pricing is reasonable, and it comes with a free tier, which is great for small projects that are right for beginner developers who want to quickly set up their apps. It can also auto scale, create new instances as needed and automatically handle high availability. App Engine gets a positive rating for performance...
AppScale - The Google App Engine Alternative
AppScale is open source Google App Engine and allows you to run your GAE applications on any infrastructure, anywhere that makes sense for your business. AppScale eliminates lock-in and makes your GAE application portable. This way you can choose which public or private cloud platform is the best fit for your business requirements. Because we are literally the GAE...

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 Google App Engine. We know about 35 links to it since March 2021 and only 26 links to Google App Engine. 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 App Engine mentions (26)

  • A Brief History Of Serverless
    In 2008, Google launched AppEngine. This product predates the formal existence of Google Cloud and can be considered Google Cloud's first offering. - Source: dev.to / about 2 months ago
  • CQL Trace Viewer: Visualizing CQL Traces with Dash
    To deploy the app, we can use Google Cloud App Engine, which is specifically built for server-side rendered websites. After we create a new project in the Google Cloud Console, we have to configure the cql-trace-viewer application. - Source: dev.to / about 1 year ago
  • Which service to host a Discord bot?
    I've read that article, but I'm thinking there are other better (and most importantly cheaper) ways of doing that, such as using App Engine (given that you have to mitigate the maximum request timeout and to make sure there are constantly exactly 1 instance running). Source: about 1 year ago
  • Using NextJs for front-end only?
    Shout out to GCP App Engine for deploying anode/Express severe. Source: about 1 year ago
  • What will Komi's resume look like?
    If your project is a bit more complicated using next.js or react.js or angular.js, you may find some free Platfrom-as-a-Service%20is%20a%20complete%20cloud%20environment,middleware%2C%20tools%2C%20and%20more.). I have seen some of my peers using free PaaS like Heroku, Vercel and I have no experience in using PaaS but I will recommend you to use PaaS from either of the three 1. Google Cloud's Google App Engine 2.... Source: about 1 year ago
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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 Google App Engine and Google BigQuery, you can also consider the following products

Salesforce Platform - Salesforce Platform is a comprehensive PaaS solution that paves the way for the developers to test, build, and mitigate the issues in the cloud application before the final deployment.

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

Dokku - Docker powered mini-Heroku in around 100 lines of Bash

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.

Heroku - Agile deployment platform for Ruby, Node.js, Clojure, Java, Python, and Scala. Setup takes only minutes and deploys are instant through git. Leave tedious server maintenance to Heroku and focus on your code.

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.