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BigQuery vs Dremio comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 18, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

BigQuery
Ranking in Cloud Data Warehouse
4th
Average Rating
8.2
Reviews Sentiment
7.3
Number of Reviews
40
Ranking in other categories
No ranking in other categories
Dremio
Ranking in Cloud Data Warehouse
9th
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
8
Ranking in other categories
Data Science Platforms (8th)
 

Mindshare comparison

As of February 2025, in the Cloud Data Warehouse category, the mindshare of BigQuery is 7.4%, down from 7.8% compared to the previous year. The mindshare of Dremio is 9.9%, up from 4.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse
 

Featured Reviews

VikashKumar1 - PeerSpot reviewer
Easy to maintain and provides high availability
Since I used BigQuery over the GCP cloud environment, I'm not sure whether we can go through internal IDEAs like IntelliJ or DBeaver that we use to connect with databases. Instead of connecting directly to BigQuery, we connect to GCP, Cloud Run, and then to BigQuery, which is a long process. Sometimes, we face some issues, bugs, and defects. We must first connect with a VPN to check data issues while working from home. Then, it allows you to connect to the cloud. After logging into the cloud, it searches for the service we are looking for, and then we go to BigQuery. This is a long process. After that, we analyze the issues in a table. Instead, it would be very helpful if it could provide a tool that we can install on our MacBook or Windows system. Once we open this tool, we can connect directly to the BigQuery server and easily perform tasks.
KamleshPant - PeerSpot reviewer
Solution offers quick data connection with an edge in computation
It's almost similar, yet it's better than Starburst in spinning up or connecting to the new source since it's on SaaS. It is a similar experience between the based application and cloud-based application. You just get the source, connect the data, get visualization, get connected, and do whatever you want. They say data reflection is one way where they do the caching and all that. Starburst also does the caching. In Starburst, you have a data product. Here, the data product comes from a reflection perspective. The y are working on a columnar memory map, columnar computation. That will have some edge in computation.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"BigQuery processes a substantial amount of data, whether in gigabytes or terabytes, swiftly producing desired data within one or two minutes."
"It has a proprietary way of storing and accessing data in its own data store and is 100% managed without you needing to install anything. There is no need to arrange for any infrastructure to be able to use this solution."
"It's straightforward to set up."
"We like the machine learning features and the high-performance database engine."
"The most valuable aspect of BigQuery is its ability to handle high data workloads without causing friction with our online systems."
"BigQuery processes a substantial amount of data, whether in gigabytes or terabytes, swiftly producing desired data within one or two minutes."
"The feature called calibrating the capacity is valuable."
"The integrated data storage features are good."
"Overall, you can rate it as eight out of ten."
"Dremio gives you the ability to create services which do not require additional resources and sterilization."
"We primarily use Dremio to create a data framework and a data queue."
"Everyone uses Dremio in my company; some use it only for the analytics function."
"Dremio is very easy to use for building queries."
"Dremio enables you to manage changes more effectively than any other data warehouse platform. There are two things that come into play. One is data lineage. If you are looking at data in Dremio, you may want to know the source and what happened to it along the way or how it may have been transformed in the data pipeline to get to the point where you're consuming it."
"It's almost similar, yet it's better than Starburst in spinning up or connecting to the new source since it's on SaaS."
"The most valuable feature of Dremio is it can sit on top of any other data storage, such as Amazon S3, Azure Data Factory, SGFS, or Hive. The memory competition is good. If you are running any kind of materialized view, you'd be running in memory."
 

Cons

"As a product, BigQuery still requires a lot of maturity to accommodate other use cases and to be widely acceptable across other organizations."
"It would be beneficial if BigQuery could be made more affordable."
"The processing capability can be an area of improvement."
"I rate BigQuery six out of 10 for affordability. It could be cheaper."
"When I execute a query, the dashboard doesn't always present the output seamlessly. Troubleshooting requires opening each pipeline individually, which is time-consuming."
"The product’s performance could be much faster."
"There is a limitation when copying data directly from BigQuery; it only supports up to ten MB when copying data to the clipboard."
"The solution hinges on Google patterns so continued improvement is important."
"Dremio doesn't support the Delta connector. Dremio writes the IT support for Delta, but the support isn't great. There is definitely room for improvement."
"They need to have multiple connectors."
"Dremio takes a long time to execute large queries or the executing of correlated queries or nested queries. Additionally, the solution could improve if we could read data from the streaming pipelines or if it allowed us to create the ETL pipeline directly on top of it, similar to Snowflake."
"There are performance issues at times due to our limited experience with Dremio, and the fact that we are running it on single nodes using a community version."
"They need to have multiple connectors. Starburst is rich in connectors, however, they are lacking Salesforce connectivity as of today."
"It shows errors sometimes."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily."
 

Pricing and Cost Advice

"The solution is pretty affordable and quite cheap in comparison to PDP or Cloudera."
"Price-wise, I think that is very reasonable."
"We are above the free threshold, so we are paying around 40 euros per month for BigQuery."
"1 TB is free of cost monthly. If you use more than 1 TB a month, then you need to pay 5 dollars extra for each TB."
"The price is a bit high but the technology is worth it."
"BigQuery is inexpensive."
"BigQuery pricing can increase quickly. It's a high-priced solution."
"One terabyte of data costs $20 to $22 per month for storage on BigQuery and $25 on Snowflake. Snowflake is costlier for one terabyte, but BigQuery charges based on how much data is inserted into the tables. BigQuery charges you based on the amount of data that you handle and not the time in which you handle it. This is why the pricing models are different and it becomes a key consideration in the decision of which platform to use."
"Dremio is less costly competitively to Snowflake or any other tool."
"Right now the cluster costs approximately $200,000 per month and is based on the volume of data we have."
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Top Industries

By visitors reading reviews
Computer Software Company
17%
Financial Services Firm
15%
Manufacturing Company
12%
Retailer
7%
Financial Services Firm
31%
Computer Software Company
10%
Manufacturing Company
8%
Retailer
4%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about BigQuery?
The initial setup process is easy.
What is your experience regarding pricing and costs for BigQuery?
The price is perceived as expensive, rated at eight out of ten in terms of costliness. Still, it offers significant cost savings.
What needs improvement with BigQuery?
When I open many of the Google Cloud products, I am in an environment that I do not feel familiar with; it is a little overwhelming. In general, if I know SQL and start playing around, it will star...
What do you like most about Dremio?
Dremio allows querying the files I have on my block storage or object storage.
What is your experience regarding pricing and costs for Dremio?
The licensing is very expensive. We need a license to scale as we are currently using the community version.
What needs improvement with Dremio?
They need to have multiple connectors. Starburst is rich in connectors, however, they are lacking Salesforce connectivity as of today. They don't have Salesforce connectivity. However, Starburst do...
 

Comparisons

 

Overview

 

Sample Customers

Information Not Available
UBS, TransUnion, Quantium, Daimler, OVH
Find out what your peers are saying about BigQuery vs. Dremio and other solutions. Updated: January 2025.
838,713 professionals have used our research since 2012.