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Number of reviews: 21
Customer Satisfaction
★★★★★★★★★★ 4.6/10
4.6
User Experience
★★★★★★★★★★ 4.9/10
4.9
Technical Foundation
★★★★★★★★★★ 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.

  • Dremio functions (BARC classification)
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 BARC Review & Rating

Provider and product description

Dremio is focused on providing a unified data lakehouse platform, leveraging Apache Iceberg for data management and catalog services. Founded in 2015 and headquartered in Santa Clara, CA, Dremio has built a reputation for delivering scalable, high-performance solutions tailored to modern data architectures.

Dremio’s platform is designed to handle the challenges of managing data across hybrid and multi-cloud environments, offering deployment capabilities both on premises and in the cloud. This includes Dremio Cloud SaaS, available on AWS and Microsoft Azure, which allows companies to manage their data with agility.

Its solutions include:

  • Data Lakehouse: A unified platform for managing structured and unstructured data.
  • Data Mesh: Solutions that promote decentralized data architecture for easier management across business units.
  • Hadoop Migration: Helping companies transition from legacy Hadoop systems to modern data architectures.

The company’s SQL engine integrates directly with Apache Iceberg, delivering fast query performance and scalability for large datasets. Dremio emphasizes cost efficiency, enabling companies to scale without excessive infrastructure expenses.

Dremio is also invested in supporting AI and machine learning development. Its platform integrates with MLOps tools, streamlining AI model creation and operationalization.

With a partner network of over 100 companies, Dremio collaborates with cloud providers, technology partners and consulting firms to expand its reach. Its global footprint includes offices in Asia, the UK and North America, employing 365 people worldwide. Dremio’s customer base includes hundreds of companies, with three of the Fortune 5 among them.

Notably, Dremio was a co-creator of Apache Arrow, a technology that has had an impact on modern data analytics by improving in-memory data processing speeds.

Strengths and challenges of Dremio

BARC’s viewpoint on the product’s strengths and challenges.

Strengths
  • Technical users highlight ease of use as their number one reason for buying Dremio at a rate of twice the average for its peers in this research.
  • Dremio was the top-ranked product in its peer group for Competitive Win Rate.
  • Dremio ranked well above the average for Functional Coverage and Performance as well as Connectivity to source and target systems.
Challenges
  • The most significant challege for users of Dremio is lack of know-how for the software.
  • In the Deployment and Operations KPI, Dremio ranked last in the Cloud Data Platforms peer group.
  • Respondents ranked Dremio’s overall partner ecosystem low.
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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
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Individual user reviews for Dremio

Role
Chief data officer
Number of employees
100 - 2.500
Industry
IT
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

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
IT
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.

Write Review
Survey Information
Number of reviews for Dremio
21
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.
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