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MongoDB Charts VS Google BigQuery

Compare MongoDB Charts VS Google BigQuery and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

MongoDB Charts logo MongoDB Charts

MongoDB Charts is the fastest and easiest way to create visualizations of MongoDB data. Connect to any MongoDB instance as a data source, create charts and graphs, build dashboards, and share them with other users for collaboration.

Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.
  • MongoDB Charts Landing page
    Landing page //
    2023-09-08
  • Google BigQuery Landing page
    Landing page //
    2023-10-03

MongoDB Charts videos

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MongoDB Charts: the easiest way to visualize document data (MongoDB World Keynote, part 5)

More videos:

  • Review - MongoDB Charts
  • Demo - MongoDB World 2019 Keynote: MongoDB Charts Demo

Google BigQuery videos

+ Add

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 MongoDB Charts and Google BigQuery)

MongoDB Charts

Google BigQuery

Data Dashboard
6 6%
Data Dashboard
94% 94
Business Intelligence
100 100%
Business Intelligence
0% 0
Big Data
0 0%
Big Data
100% 100
Data Visualization
100 100%
Data Visualization
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare MongoDB Charts and Google BigQuery

MongoDB Charts Reviews

We have no reviews of MongoDB Charts 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...
Source: www.shipyardapp.com
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.
Source: www.analytixlabs.co.in

Social recommendations and mentions

Based on our record, Google BigQuery seems to be more popular. It has been mentiond 35 times since March 2021. 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.

MongoDB Charts mentions (0)

We have not tracked any mentions of MongoDB Charts yet. Tracking of MongoDB Charts recommendations started around Mar 2021.

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 / 8 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 / 8 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 / 9 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: 10 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: 10 months ago
View more

What are some alternatives?

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

Metabase - Metabase is the easy, open source way for everyone in your company to ask questions and learn from...

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

Holistics.io - Holistics is a powerful BI platform that empowers analysts with SQL to build a data warehouse and automated reporting routines that deliver data to everyone. Get your first report within 10 minutes! Sign-up for a free trial!

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.

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

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.

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