Customer Satisfaction

★★★★★★★★★★ 4.6/10

4.6

User Experience

★★★★★★★★★★ 4.9/10

4.9

Functionality

★★★★★★★★★★ 4.4/10

4.4

Business Value

★★★★★★★★★★ 6.5/10

6.5

Dremio

What is Dremio?

Dremio is a SQL-based query engine on Hadoop and cloud storage systems, with optimized services/products such as Dremio Sonar for data warehousing and Dremio Arctic as Apache Iceberg Lakehouse Catalog. Available in the cloud or on-premise.

Data Management & Storage

● Databases & Access Engines

● Data Intelligence, Data Catalogs and Marketplaces

– Data Operations

– Data Pipelining and Data Quality

● = covered

About Dremio

Self-description of the vendor

No vendor self-description available

References

No data available

Partners

No data available

Dremio User Reviews & Experiences

The information contained in this section is based on user feedback and actual experience with Dremio.

The information and figures are largely drawn from BARC’s The BI & Analytics Survey, The Planning Survey, The Financial Consolidation Survey and The Data Management Survey. You can find out more about these surveys by clicking on the relevant links.

Who uses Dremio in a data management context and how

Why users buy Dremio and what problems they have using it

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Full user reviews and KPI results for Dremio

All key figures for Dremio at a glance.

Premium content. Unlock with BARC+.

For just €79 per month (€948 per year) you can access all the paid content on www.barc.com.

Your benefits:

Get independent information on software solutions, market developments and trends in data, analytics, business intelligence, data science and corporate performance management.
Make data & analytics decisions based on numbers, data, facts and expert knowledge
Access to all premium articles and all our research, including all software comparison studies, scores and surveys.
Unlimited access to the BARC media library
Consume unlimited content anywhere

Individual user reviews for Dremio

Role

Project manager for BI/analytics from IT

Number of employees

More than 2.500

Industry

Process industry

Source

Invited by the vendor, The Data Management Survey 25, 04/2024

What do you like best?

Integration in die bestehende Landschaft. Wir haben es geschafft die gesamte Kette von Test bis in Produktion zu automatisieren mit minmaler Downtown. Einstiegshürde für Anwender / Fachanwender sehr niedrig.

What do you like least/what could be improved?

Produktzyklen in Sinne von technischen Anpassungen und Veränderungen zu langsam.

What key advice would you give to other companies looking to introduce/use the product?

Bei SaaS sich genau mit der Automatisierung und Bereitstellung auseinander zu setzen. Die Einmal inverstierte Zeit wird vielfach wieder reingeholt.

How would you sum up your experience?

Vom ersten Prototypen bis hin zu einem vollständigen automatisierten Deployment gute und stetige Betreuung.

Role

Consultant

Number of employees

More than 2.500

Industry

Source

Invited by the vendor, The Data Management Survey 25, 03/2024

What do you like best?

Sehr übersichtliche UI, gute UX. Super schnelle Umsetzung von neuen Datenprodukten ohne große ETL-Prozesse.

What do you like least/what could be improved?

Kubernetes Unterstützung (Helm-Chart ist ausbaufähig). Integration in IaC Tools wie Terraform. Anbindung an Data Science Tools wie Jupyter Notebooks.

What key advice would you give to other companies looking to introduce/use the product?

Einfach mal mit dem Open-Source Produkt starten und erste Erfahrungen sammeln.

How would you sum up your experience?

Verglichen mit ähnlichen Tools gefällt mir das gesamte Zusammenspiel und der Funktionsumfang und ich bin sehr zufrieden mit den Tool.

Role

Project manager for BI/analytics from IT

Number of employees

100 - 2.500

Industry

Utilities

Source

Invited by the vendor, The Data Management Survey 25, 04/2024

What do you like best?

Die Einfachheit im Umgang mit Daten und das Gesamtdesign.

What do you like least/what could be improved?

Automatische erstellte Reflections erfüllen nicht die Erwartungen, da sich über mehrere Datenschichten Inkonsistenzen ergeben. Stabiler Betrieb der Dremio-Executoren, auf Mikoaoft AKS, ist nicht ausreichend.

What key advice would you give to other companies looking to introduce/use the product?

Reflections ausschließlich über APIs triggern.

How would you sum up your experience?

Erwartungen haben sich letztlich aufgrund technischer Schwierigkeiten nicht erfüllt.

Role

Data engineer/Data manager

Number of employees

More than 2.500

Industry

Manufacturing

Source

BARC Marketing, The Data Management Survey 25, 04/2024

What do you like best?

SQL Interface. DBT Connectivity. Iceberg.

What do you like least/what could be improved?

User Interface. Administration / RBAC.

What key advice would you give to other companies looking to introduce/use the product?

Force templated workspaces on users Enforce Version Control / Git via e.g. DBT.

How would you sum up your experience?

Good software with it quirks. More (business-) user friendly than all competitors that we evaluated.

Role

Chief data officer

Number of employees

100 - 2.500

Industry

Source

BARC Marketing, The Data Management Survey 25, 04/2024

What do you like best?

Love the no ETL approach to accessing data. We leverage Spark/Scala process for sourcing and handling data. Once we target into Iceberg and nessie sources are automatically available in Dremio for team access. No ETL required to provision and load like traditional (or Snowflake for that matter), while providing FAST query response to cross region data sets.

What do you like least/what could be improved?

So far no issues. Billing transparency could be improved for self hosted customers. If adopting the full SaaS model this is available, but understanding and projecting DCU usage is a little challenging in the current self hosted model. This may be an AWS hosted challenge though and not an issue with Dremio itself.

What key advice would you give to other companies looking to introduce/use the product?

Have a clear set of objectives you are looking to accomplish and then select the tool that best enables these vs starting with tools and attempting to warp the tool to meet future needs.

How would you sum up your experience?

Very positive so far. We are loading around 1TB every 3 days and the platform is handling it nicely! Very scalable and fast response times.

Role

Consultant

Number of employees

100 - 2.500

Industry

Manufacturing

Source

BARC Marketing, The Data Management Survey 25, 04/2024

What do you like best?

Lakehouse. Security. Performance.

What do you like least/what could be improved?

Labels (impossible to move around labels, to have a list of pre defined labels). Search (impossible to search within the data). Moving / saving VDS in folders (selection of the whole path each time even though we are creating the VDS in the folder, can't move easily a whole folder to another path).

What key advice would you give to other companies looking to introduce/use the product?

To set up a POC to see if it fit their needs.

How would you sum up your experience?

Good

Survey Information

Number of reviews for Dremio

Reviewed versions

100 percent version 24

Peer groups in the survey

Cloud Data Platforms, Data Product Engineering, Data Product Engineering (Big Players)

Interactive comparison of data tools

Compare data tools and software with our interactive self-service tool, The Data Management Survey Analyzer.