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Google BigQuery VS Databricks

Compare Google BigQuery VS Databricks and see what are their differences


A fully managed data warehouse for large-scale data analytics.

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

Google BigQuery details

Categories
Data Dashboard Database Tools Big Data
Website cloud.google.com  

Databricks details

Categories
Data Dashboard Database Tools Big Data Analytics
Website databricks.com  

Google BigQuery videos

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Databricks videos

Introduction to Databricks

More videos:

  • - Databricks - Data Movement and Query
  • - Azure Databricks Tutorial | Data transformations at scale

Category Popularity

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Social recommendations and mentions

We have tracked the following product recommendations or mentions on Reddit and HackerNews. They can help you identify which product is more popular and what people think of it.

Google BigQuery mentions

  • Using BigQuery Public Datasets to research the impact of COVID-19 🦠
    BigQuery is a serverless big data warehouse available as a part of Google Cloud Platform. It's highly scalable, meaning that it can process tiny datasets as well as petabytes of data in seconds, using more cloud capacity as needed. (However, due to BigQuery's distributed architecture, you can't possibly expect it to have a sub-second query response time.). - Source: dev.to / 4 months ago
  • Scraping repositories related to a university
    Alternatively, you can look into Google Cloud BigQuery (https://cloud.google.com/bigquery). There is a limit on how much data that can be processed per month with a free account although they do provide a $300 credit. They have a public GitHub repos data set here: https://console.cloud.google.com/marketplace/product/github/github-repos. This is an example on how the dataset can be used:... - Source: Reddit / 3 months ago
  • Google Cloud just posted this on their Twitter
    "Google Cloud’s databases and analytics products such as BigQuery, Dataflow, Pub/Sub and Firestore brought Theta Labs unlimited scale and performance, allowing them to: ...". - Source: Reddit / 3 months ago
  • Analytics Projects in Programmatic Space
    Https://cloud.google.com/bigquery#section-8 - Store all programmatic log levels on Google Bigquery, Build and deploy a propensity to purchase a model for predicting customer purchasing behavior using BigQuery ML and AI Platform. - Source: Reddit / about 2 months ago

Databricks mentions

What are some alternatives?

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

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.

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.

Presto DB - Distributed SQL Query Engine for Big Data (by Facebook)

Hadoop HDFS - The Apache HDFS is a distributed file system that makes it possible to scale a single Apache Hadoop cluster to hundreds (and even thousands) of nodes.

Rakam - Custom analytics platform

Concurrent - Concurrent is a technology solution providing real-time computing solutions for businesses and individuals.

User reviews

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