Software Alternatives & Reviews

Teradata VS Google BigQuery

Compare Teradata VS Google BigQuery and see what are their differences

Teradata logo Teradata

See why Teradata is the world's leading provider of business analytics solutions, data and analytics solutions, and hybrid cloud products and services.

Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.
  • Teradata Landing page
    Landing page //
    2023-09-22
  • Google BigQuery Landing page
    Landing page //
    2023-10-03

Teradata

Categories
  • Databases
  • Relational Databases
  • NoSQL Databases
  • Network & Admin
Website teradata.com
Pricing URL Official Teradata Pricing
Details $-

Google BigQuery

Categories
  • Data Management
  • Data Warehousing
  • Data Dashboard
  • Database Tools
  • ETL
  • Big Data
Website cloud.google.com
Pricing URL-
Details $

Teradata videos

TechBytes: Teradata Vantage

More videos:

  • Review - Teradata Company Profile

Google BigQuery videos

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

+ Add video

Category Popularity

0-100% (relative to Teradata and Google BigQuery)
Tool
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Databases
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 Teradata and Google BigQuery

Teradata Reviews

16 Top Big Data Analytics Tools You Should Know About
Teradata is one of the most popular Relational Database Management System (RDBMS) developed by the company named Teradata itself.

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 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.

Teradata mentions (0)

We have not tracked any mentions of Teradata yet. Tracking of Teradata 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 / 7 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 / 8 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
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What are some alternatives?

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

Datomic - The fully transactional, cloud-ready, distributed database

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

DynamoDB - Amazon DynamoDB is a fast and flexible NoSQL database service for all applications that need consistent, single-digit millisecond latency at any scale. It is a fully managed cloud database and supports both document and key-value store models.

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.

MarkLogic Server - MarkLogic Server is a multi-model database that has both NoSQL and trusted enterprise data management capabilities.

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.