No more typing reviews! Try our Samantha, our new voice AI agent.

AtScale Adaptive Analytics (A3) vs Dremio comparison

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

AtScale Adaptive Analytics ...
Average Rating
5.0
Number of Reviews
1
Ranking in other categories
Data Virtualization (7th), BI (Business Intelligence) Tools (50th), Data Governance (45th), BI on Hadoop (1st)
Dremio
Average Rating
8.4
Reviews Sentiment
6.6
Number of Reviews
11
Ranking in other categories
Cloud Data Warehouse (8th), Data Science Platforms (10th)
 

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. AtScale Adaptive Analytics (A3) is designed for Data Virtualization and holds a mindshare of 6.1%, down 8.7% compared to last year.
Dremio, on the other hand, focuses on Data Science Platforms, holds 2.2% mindshare, down 4.2% since last year.
Data Virtualization Mindshare Distribution
ProductMindshare (%)
AtScale Adaptive Analytics (A3)6.1%
Denodo22.1%
TIBCO Data Virtualization15.0%
Other56.8%
Data Virtualization
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Dremio2.2%
Databricks8.2%
Dataiku5.6%
Other84.0%
Data Science Platforms
 

Featured Reviews

it_user822762 - PeerSpot reviewer
Senior BI and Reporting Analyst at a financial services firm with 10,001+ employees
The GUI interface is nice and easy to use, but the organization of the icons is not saved across users
Connecting to a Hadoop database to create a cube to connect to Tableau. We want to be able to easily create cubes which can be connected to Tableau for visualization The product had many issues. We had great collaboration with the product development team, but the product was not able to meet our…
Corrr Moray - PeerSpot reviewer
SR BI developer at BRQ Digital Solutions
Has simplified complex data integration workflows and supported consistent reporting across multiple sources
We also have a close relationship with the team that does the Dremio maintenance for the database, like upgrading the versions and they know about some specific problems we had in the past, such as a memory leak. We had a memory leak on some versions, which sometimes stopped the service. Since we are using Dremio installed like a server, not a SaaS solution, many times we need to stop and restart the service to clear all the cache and all that, and this is the thing I should add. I see that many times the new versions of Dremio have not fixed old bugs, and in some new versions, old problems that were previously fixed come back again, so I think the upgrade part could use improvement. I remember using some features in the past, like pivot tables, which proved to be really difficult, but I know this is a fault also for other vendors. Pivoting, transposing, and unpivoting are often not so good. CTEs also many times prove to be not so good, so I think these two main items could be improved significantly if they standardize them.

Quotes from Members

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

Pros

"The GUI interface is nice and easy to use."
"The GUI interface is nice and easy to use."
"Dremio has positively impacted my organization by helping us create a single source of truth, a singular data warehouse where we can have access to all of the data sets."
"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."
"Dremio has positively impacted my organization as nowadays we are connected to multiple databases from multiple environments, multiple APIs, and applications, and Dremio organizes everything in an amazing way for me."
"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."
"Dremio is very easy to use for building queries."
"Everyone uses Dremio in my company; some use it only for the analytics function."
"Overall, you can rate it as eight out of ten."
"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."
 

Cons

"The product was not able to meet our 10 second refresh requirements."
"The organization of the icons is not saved across users."
"The product was not able to meet our 10 second refresh requirements."
"There was an issue with the incremental aggregation not working as indicated."
"We had a memory leak on some versions, which sometimes stopped the service."
"They need to have multiple connectors."
"They need to have multiple connectors. Starburst is rich in connectors, however, they are lacking Salesforce connectivity as of today."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"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."
"They have an automated tool for building SQL queries, so you don't need to know SQL. That interface works, but it could be more efficient in terms of the SQL generated from those things. It's going through some growing pains. There is so much value in tools like these for people with no SQL experience. Over time, Dermio will make these capabilities more accessible to users who aren't database people."
"Dremio takes a long time to execute large queries or the executing of correlated queries or nested queries."
"It shows errors sometimes."
 

Pricing and Cost Advice

Information not available
"Right now the cluster costs approximately $200,000 per month and is based on the volume of data we have."
"Dremio is less costly competitively to Snowflake or any other tool."
report
Use our free recommendation engine to learn which Data Virtualization solutions are best for your needs.
893,221 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Healthcare Company
13%
Financial Services Firm
11%
Computer Software Company
10%
Manufacturing Company
10%
Financial Services Firm
26%
Computer Software Company
8%
Healthcare Company
6%
Comms Service Provider
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business1
Midsize Enterprise5
Large Enterprise5
 

Questions from the Community

Ask a question
Earn 20 points
What is your experience regarding pricing and costs for Dremio?
I don't have information about pricing, setup cost, and licensing for Dremio, so I am not entitled to discuss it.
What needs improvement with Dremio?
I wouldn't say there is anything Dremio can be improved on. If I could change something, I would say many developers and programmers, when they are starting to work in this specific field or area, ...
What is your primary use case for Dremio?
I have been using Dremio for a year and a half. My main use case for Dremio is that I am able to access multiple databases and I can easily and quickly connect Dremio with my dashboards. In my rece...
 

Also Known As

AtScale, AtScale Intelligence Platform
Dremio AWS - BYOL
 

Overview

 

Sample Customers

Rakuten, TD Bank, Aetna, Glaxo-Smith Kline, Biogen, Toyota, Tyson
UBS, TransUnion, Quantium, Daimler, OVH