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AtScale Adaptive Analytics (A3) vs Dremio comparison

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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 (44th), Data Governance (41st), BI on Hadoop (1st)
Dremio
Average Rating
8.4
Reviews Sentiment
6.5
Number of Reviews
14
Ranking in other categories
Cloud Data Warehouse (10th), Data Science Platforms (9th)
 

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 7.1%, up 5.9% compared to last year.
Dremio, on the other hand, focuses on Data Science Platforms, holds 2.0% mindshare, down 2.9% since last year.
Data Virtualization Mindshare Distribution
ProductMindshare (%)
AtScale Adaptive Analytics (A3)7.1%
Denodo24.5%
SAP HANA18.3%
Other50.099999999999994%
Data Virtualization
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Dremio2.0%
Databricks6.5%
Dataiku4.4%
Other87.1%
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…
Baptiste Bergelin - PeerSpot reviewer
Data Architect at a consultancy with 51-200 employees
Data platform has unified diverse sources for mesh use but has needed query cache tuning
We contact the technical support at least weekly; currently, it's more or less daily because we face performance issues, crashes of queries sometimes, and we also need support for configuration of the query engines and so on. We are using the support extensively, and we are under a Gold support plan. The quality and speed of the support are satisfactory. Sometimes it depends on which support engineer is taking up the case, but very often it's quite responsive, reactive, coherent, and the response is of good quality. I would give the support an eight on a scale from one to ten, with ten being the highest.

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 first feature that stands out for me in Dremio is the federated type of query, which allows the possibility to use multiple endpoints without worrying about writing custom SQL that runs only for SQL Server or for Postgres and Redshift."
"Dremio is very easy to use for building queries."
"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."
"Dremio has positively impacted my organization by creating faster development and POC projects."
"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."
"Reflections pre-calculate results which are then just delivered instantly, meaning you do not need to wait to run a query for a longer time on huge amounts of data, and the user gets very quick answers."
"Dremio allows querying the files I have on my block storage or object storage."
 

Cons

"The organization of the icons is not saved across users."
"There was an issue with the incremental aggregation not working as indicated."
"The product was not able to meet our 10 second refresh requirements."
"One area where Dremio can be improved is the lack of tooling or functionalities for importing data in a pipeline way, as it is not an ETL or ELT component."
"We had a memory leak on some versions, which sometimes stopped the service."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"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."
"Dremio could be improved by making it easier for data cataloging, especially when working with open table formats, as you have to choose a data format and then go into it."
"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."
"Many developers and programmers, when they are starting to work in this specific field or area, are much more used to SQL Server, the Microsoft way of querying, and Dremio has some features that are different when we are talking about the syntax of coding, so I would improve that."
 

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."
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Use our free recommendation engine to learn which Data Virtualization solutions are best for your needs.
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Top Industries

By visitors reading reviews
Comms Service Provider
15%
Healthcare Company
13%
Manufacturing Company
13%
Construction Company
10%
Financial Services Firm
21%
Outsourcing Company
9%
Comms Service Provider
8%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise6
Large Enterprise5
 

Questions from the Community

Ask a question
Earn 20 points
What is your experience regarding pricing and costs for Dremio?
I chose eight out of ten because Dremio is expensive for the Enterprise version, particularly regarding licensing.
What needs improvement with Dremio?
I think Dremio can be improved to query faster than multiple sources and big data lakehouses. The community version could be updated for new data catalog connections. I think the documentation is s...
What is your primary use case for Dremio?
I have been using Dremio to select multiple data sources, retrieve multiple data sources, and create and maintain Iceberg tables for the data lakehouse. My main use case for Dremio is to actively c...
 

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