Software Alternatives, Accelerators & Startups

Google Tag Manager VS Google BigQuery

Compare Google Tag Manager VS Google BigQuery and see what are their differences

Google Tag Manager logo Google Tag Manager

Google Tag Manager helps make tag management simple, easy and reliable by allowing marketers and webmasters to deploy website tags all in one place.

Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.
  • Google Tag Manager Landing page
    Landing page //
    2021-07-29
  • Google BigQuery Landing page
    Landing page //
    2023-10-03

Google Tag Manager videos

What Is Google Tag Manager? Top 3 Reasons You Need It (Google Tag Manager Review)

More videos:

  • Review - Introduction To Google Tag Manager 2020 | Lesson 1 (GTM for Beginners)
  • Review - Why You Shouldn't Use Google Tag Manager: Google Tag Manager Introduction

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 Tag Manager and Google BigQuery)
Analytics
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Web Analytics
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 Tag Manager and Google BigQuery

Google Tag Manager Reviews

We have no reviews of Google Tag Manager yet.
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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

Based on our record, Google BigQuery seems to be a lot more popular than Google Tag Manager. While we know about 35 links to Google BigQuery, we've tracked only 3 mentions of Google Tag Manager. 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 Tag Manager mentions (3)

  • 5 WEBSITES TIPS TO SUPERCHARGE YOUR BUSINESS GROWTH- Creative Wave Tech
    Design a change global positioning framework, for example, Google Tag Manager and Google Analytics objectives and occasions, to log transformations and client ways (you can gain proficiency with about how to do that in our post, The Top 12 Website KPIs for Small Business). Source: over 2 years ago
  • 4 Reasons Why Data Engineers Hate Google Tag Manager
    For years, Google Tag Manager (GTM) has made it easy for marketers and analysts to install and manage third-party analytics and marketing tools on their websites and apps. It provides a centralized platform allowing non-technical team members to add, edit, and disable tags without having to touch the source code. This means they don't have to bug you to add new tags or edit existing ones in the event of an update. - Source: dev.to / over 2 years ago
  • Graph database question?
    For C360 implementations the there’s a tool called Segment (https://segment.com/) that unifies all the customer identities used across websites/phone apps. Within Segment there is a defined matching logic for identity resolution based on different keys used across apps such as User ID, email, phone number, address, social media account. The end result is each persona will have one Segment ID where all your traits... Source: about 3 years ago

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 / 9 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 / 9 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 / 10 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: 11 months 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: 12 months ago
View more

What are some alternatives?

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

Google Analytics - Improve your website to increase conversions, improve the user experience, and make more money using Google Analytics. Measure, understand and quantify engagement on your site with customized and in-depth reports.

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

Adobe Analytics - Adobe Analytics is an industry-leading solution that empowers you to understand your customers as people and steer your business with customer intelligence.

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.

Mixpanel - Mixpanel is the most advanced analytics platform in the world for mobile & web.

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.