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Number of reviews: 19
Customer Satisfaction
★★★★★★★★★★ 8.2/10
8.2
User Experience
★★★★★★★★★★ 8.7/10
8.7
Technical Foundation
★★★★★★★★★★ 7.3/10
7.3
Business Value
★★★★★★★★★★ 7.4/10
7.4

dbt Cloud

What is dbt Cloud?

Development environment for creating SQL-based transformations with support for software development processes such as modularity, portability, CI/CD and documentation.

  • dbt Cloud functions (BARC classification)
Data Management & Storage
– Databases & Access Engines
– Data Intelligence, Data Catalogs and Marketplaces
● Data Operations
● Data Pipelining and Data Quality

● = covered

About dbt Cloud

Self-description of the vendor

No vendor self-description available
References
No data available
Partners
No data available

dbt Cloud BARC Review & Rating

Provider and product description

Eight years ago, Tristan Handy and two analytics colleagues started a consulting venture to help companies transform data using new open-source software they named “data build tool” or dbt. They aimed to empower new “analytics engineers” that prepare data for analysts, thereby easing the burden on traditional data engineers. As adoption grew, these consultants introduced commercial software, giving birth to dbt Labs as a software vendor.

dbt Labs now serves 4,600 customers, including Conde Nast, Siemens and a wide range of cloud-native startups. It has raised $416 million from backers such as Altimeter, Databricks, Snowflake and Salesforce Ventures. Its partner ecosystem includes Fivetran for ingestion, Alation for cataloging, Monte Carlo for data observability, and Rudderstack for customer data management. dbt’s open-source community has swelled to 100,000 users.

dbt Cloud helps analytics engineers clean, model, test, deliver, observe and document data products using principles of continuous integration and continuous delivery (CI/CD). By writing SQL select statements, for example, they can create interconnected models that populate data warehouse tables and views, which is particularly valuable for data-driven companies with a scripting preference. dbt’s semantic layer then presents analytics-ready data for BI reporting, dashboards, ML models and data-driven applications that run on cloud platforms.

Strengths and challenges of dbt Cloud

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

Strengths
  • A large and growing user community, especially data engineers with tech-savvy startups, rely on open-source dbt for data transformation in support of BI and AI/ML projects. They recognize dbt Labs as a pioneer and thought leader in the field of analytics engineering.
  • By nearly every measure, dbt Cloud outranks its peers as the industry’s preferred ETL tool. Technical users appreciate its ease of use, functionality and performance.
  • dbt Cloud delights customers across tool categories with its user experience and ecosystem support. The product vision and roadmap meet their requirements and align well with the technology landscape.
Challenges
  • dbt Cloud has frustrated a higher portion of customers with its rising, inflexible prices than industry peers.
  • Because it focuses on analytics engineering and data preparation, dbt Labs is unable to compete for the business of large enterprises that prefer data management suites rather than point tools.
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dbt Cloud User Reviews & Experiences

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

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 dbt Cloud in a data management context and how

Why users buy dbt Cloud and what problems they have using it

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Full user reviews and KPI results for dbt Cloud

All key figures for dbt Cloud 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.
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Individual user reviews for dbt Cloud

Role
Data engineer/Data manager
Number of employees
More than 2.500
Industry
Retail
Source
Invited by the vendor, The Data Management Survey 25, 04/2024
What do you like best?

Automatische Lineage (besonders die neue Column Level Lineage). Leicht zu konfigurierende Datenqualitätstests. Flexibilität beim Deployment (Ziel-Datenbank/Schema der Models). Recht komfortabler Editor (z.B. Macro-Shortcuts, Quoting). Schnelle Erreichbarkeit der wichtigsten Befehle (run, test, build, lint/fix) per Knopfdruck.

What do you like least/what could be improved?

Ggleichzeitige Arbeit in mehreren Projekten parallel (in verschiedenen Browser-Tabs) schwierig bzw. kaum möglich. Feature Degression: früher konnte man mit SQLFluff einzelne Regeln gezielt hintereinander fixen; seit kurzen wird nur noch Fix all issues angeboten. (Noch?) keine einfach Möglichkeit, ein Modell nur einmalig zu bauen (z.B. historische Fakten). Es gibt zwar Workarounds, aber wünschenswert wäre eine Config-Option wie materialized = table_if_not_exists. Lineage bei Verwendung von dbt mesh funktioniert nur bis zum Mesh-Model, aber nicht upstream (also die Lineage für das verwendete Model aus einem anderen Projekt). Dedizierter PK-Test wäre wünschenswert (statt Kombination aus unique + not_null). Könnte man git blame in die Editor-UI integrieren (ähnlich wie z.B. in VS Code)?

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

Onboarding/Training in einem separaten Playground-Projekt. Die Konfigurationsfreiheiten (Ordnerstruktur, globaler Namensraum etc.) noch vor Projektstart per Konventionen eindämmen (und dabei großzügig offizielle Best Practices an eigene Bedürfnisse anpassen). Akzeptanz bei Usern bzw. Entwicklern steigern: die Vorteile (einfaches Testing, automatische Lineage, flexibles Deployment, Compile -Funktionalität für copy&paste-fähigen Code) an konkreten echten Beispielen demonstrieren bzw. selbst erfahren lassen.

How would you sum up your experience?

Überwiegend positiv; manche Features (einfaches Testing, automatische Lineage) möchte ich nicht mehr missen. Das Marketing-Material konnte mich zuvor nicht überzeugen, da es solche Features zwar erwähnt, aber nicht in der Lage ist, die tatsächliche Nützlichkeit vorzustellen (das erlebte ich erst beim praktischen Erstkontakt mit dem Tool).

Role
Project manager for BI/analytics from business department
Number of employees
100 - 2.500
Industry
Telecommunications
Source
Invited by the vendor, The Data Management Survey 25, 04/2024
What do you like best?

Das Onboarding und Enablement des Teams war sehr gut.

What do you like least/what could be improved?

Keine aktuellen Themen bekannt.

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

Evaluierung gegenüber alternativen Lösungen empfehlenswert, um die Funktionsfähigkeit sicherzustellen.

How would you sum up your experience?

Der Wechsel des Transformation Tools zu DBT hat recht reibungslos funktioniert.

Role
Lead Data Warehouse Architect
Number of employees
100 - 2.500
Industry
Utilities
Source
Invited by the vendor, The Data Management Survey 25, 05/2024
What do you like best?

User Interface.

What do you like least/what could be improved?

Umbenennungen in referenzierte Objekten propagieren.

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

DWH-Spezialisten suchen!

How would you sum up your experience?

Einfach gut!

Role
CIO
Number of employees
More than 2.500
Industry
Healthcare
Source
Invited by the vendor, The Data Management Survey 25, 04/2024
What do you like best?

Tool built by those in the field, for those in the field.

What do you like least/what could be improved?

-

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

Invest in upskilling of the workforce.

How would you sum up your experience?

Great company with great leadership.

Role
Data engineer/Data manager
Number of employees
More than 2.500
Industry
Healthcare
Source
Invited by the vendor, The Data Management Survey 25, 05/2024
What do you like best?

Core functionality of the product is good. Training and support. General conduct of support and sales teams.

What do you like least/what could be improved?

Pricing model. Not as flexible as we would like. Expensive to scale up - should be a tiered model with discount applied with further adoption.

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

-

How would you sum up your experience?

The cost of dbt Cloud makes dbt Core an attractive option. There needs to be more differentiators in the Cloud product for consumers to justify the price.

Role
Enterprise architect
Number of employees
More than 2.500
Industry
Process industry
Source
Invited by the vendor, The Data Management Survey 25, 05/2024
What do you like best?

Great ecosystem integration, de-facto industry standard for developing data products on Snowflake.

What do you like least/what could be improved?

Interface that is more friendly for business-end-users. E.g. with self-service data modelling based on existing data products.

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

-

How would you sum up your experience?

We are at the beginning, but looks good so far!

Role
Data engineer/Data manager
Number of employees
More than 2.500
Industry
Telecommunications
Source
Invited by the vendor, The Data Management Survey 25, 05/2024
What do you like best?

The business problem it is solving.

What do you like least/what could be improved?

Cost for dbt Cloud developer seats.

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

Seriously consider dbt Cloud over dbt core. The initial licence cost will likely be offset by dev cost of maintaining core depending on your org.

How would you sum up your experience?

-

Role
Data engineer/Data manager
Number of employees
More than 2.500
Industry
Media/Publishing
Source
Invited by the vendor, The Data Management Survey 25, 04/2024
What do you like best?

Wiedervendbarkeiten (Macro) und Flexibilität bei der Programmierung (Jinja, Python, SQL). Integration in die die Datenbank und git.

What do you like least/what could be improved?

Data Ingest muss vorgelagert mit separater Lösung erfolgen, mindestens bis nach GCS (Google Storage).

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

-

How would you sum up your experience?

Durchweg positiv, sowohl das Tool an sich wie auch den Support und die Kundenbetreuung.

Write Review
Survey Information
Number of reviews for dbt Cloud
19
Reviewed versions
44 percent version 1.8, 38 percent version 1.7, 19 percent version 1.6
Peer groups in the survey
Data Product Engineering, Data Product Engineering (Big Players), ETL Tools
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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