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Google BigQuery

Big Improvements for Google BigQuery Analytics with Chartio

Many of our customers use BigQuery as their data warehouse. Google’s BigQuery is an excellent option for many companies because it requires no infrastructure to manage, can store petabytes of data, and uses SQL as its query language. It also works great with Chartio! Here are some of our latest features and support for BigQuery in our Chartio product.

Building a Data Stack: An Overview on Google BigQuery

Get an overview on Google BigQuery the petabyte-scale and cloud-based data warehouse from Google. This blog post will cover concurrency, throughput, security, data operations and cost for Google BigQuery. Read to learn more.

Calculating Your Data Warehouse Cost

As data becomes more voluminous, accessible and cost efficient—businesses must leverage data for their advantage. Learn how to calculate the cost of popular data warehouse solutions including Amazon Redshift and Google BigQuery.

An Overview on Amazon Redshift and Google BigQuery Security

In this blog post, we cover features that Amazon Redshift and Google BigQuery provide to manage data warehouse security for their customers.

Warehouse Maintenance: Amazon Redshift and Google BigQuery

Examine the differences in how cloud-based Amazon Redshift and Google BigQuery perform maintenance on their cloud-based systems, which is often seen as a point of contention for many users. Read about the differences.

How to Load Data into Amazon Redshift or Google BigQuery

In this blog post, examine how data warehouses Amazon Redshift and Google BigQuery handle how data loads, its speed, accessibility, and more.

How Amazon Redshift and Google BigQuery Handle Provisioning

Data warehouses, like Amazon Redshift and Google BigQuery, are meant to handle a large volume of data. Read this blog post as we examine how Amazon Redshift and Google BigQuery handle data provisioning.

Impact of Throughput and Concurrency on Your Data Warehouse

In this blog post, we discuss throughput and concurrency on your data warehouse and the impact it has on your ability to run analyses.

Choosing Between Amazon Redshift and Google BigQuery

Choosing a data warehouse that meets your business needs doesn't have to be difficult. Read our white paper examining the differences between cloud-based, data warehouse leaders Amazon Redshift and Google BigQuery.

Leveraging Your Data Warehouse as a Competitive Advantage

Data warehouses are optimized to analyze data by turning massive amounts of data into analytics that are easy to understand. Learn the advantages in using a data warehouse for analysis and how they are a competitive advantage.

When to Invest in a Data Warehouse

A data warehouse, or a reporting database, is an online analytical processing (OLAP) database and acts as a layer on top of an operational database. Learn when you should invest in a data warehouse for your data stack.