Developer
Free
- One Developer seat
- 3,000 successful models built per month
- 1 project
- Browser-based IDE
- Multi-factor authentication (MFA)
- Job scheduling and monitoring
- CI checks on Github and GitLab
- Upgrade to the latest dbt release automatically
Overview
dbt (data build tool) is an open-source data transformation tool that enables data teams to build and manage data pipelines using SQL. It allows users to transform data in their warehouse by writing select statements, which dbt then compiles into tables and views. This approach brings software engineering best practices, such as modularity, testing, and version control, to data analytics.
How dbt Works
Users define data models as SQL queries, which dbt executes against their data warehouse. Key functionalities include:
- SQL-based Transformation: Build data pipelines using native SQL comprehension and local validation.
- Interactive Lineage: Visualize data flow and transformations across projects with a live and interactive Directed Acyclic Graph (DAG), including column-level lineage.
- Automated Refactoring: Deep SQL awareness automatically updates downstream references when models or columns are renamed, ensuring project consistency.
- Interoperability: Integrates with a wide ecosystem of data platforms and tools, leveraging open standards without storing user data.
dbt helps improve data quality, strengthen governance, and foster collaboration, allowing teams to deliver trusted analytics and AI products more rapidly. It also optimizes costs by intelligently orchestrating production pipelines, building only necessary models and saving on compute resources.
Key features
- Transform data with SQL
- Interactive lineage across projects and columns
- Automatically refactor models and columns
- Deep ecosystem integrations and open standards
- Improve data quality and trust
- Drive efficiency and reduce cost
- Build better AI with higher-quality data
- Smarter orchestration saves on warehouse spend
Who uses it
Data teams, data leaders, and practitioners, including analytics engineers, data scientists, and developers, who build and manage data models and pipelines.
Pros
- Enables modular, tested, and version-controlled data pipeline development using SQL.
- Provides interactive data lineage across projects and columns for better understanding.
- Automates refactoring of models and columns, maintaining project consistency.
- Offers deep ecosystem integrations and adheres to open standards for flexibility.
- Improves data quality, governance, and trust for analytics and AI development.
- Optimizes warehouse spend through smarter orchestration of production pipelines.
Cons
- Requires proficiency in SQL for effective data transformation and modeling.
- Primarily focuses on the "T" (transformation) in ETL, requiring other tools for extraction and loading.
- Detailed pricing plans are not transparently displayed on the main website.
- May present a learning curve for teams new to analytics engineering methodologies.
Our take
dbt serves as a robust platform for data transformation, enabling data teams to build and manage data models efficiently. Its emphasis on SQL-based development and data governance makes it suitable for complex analytical and AI data preparation workflows.
Pricing plans
Starter
$100 per user/month
- Five developer seats
- 15,000 successful models built per month
- 5,000 queried metrics per month
- 1 project
- All features in Developer, plus
- Lineage with dbt Catalog
- Define & query metrics with dbt Semantic Layer
- dbt Semantic Layer basic
- API access
Enterprise
Custom Pricing
- Custom Developer seat count
- 100,000 successful models built per month
- 20,000 queried metrics per month
- 30 projects
- All features in Starter, plus
- Column-level lineage in dbt Catalog
- Governed metrics with caching
- Multi-project architecture (dbt Mesh)
- SSO, Role-Based Access Control, and SCIM provisioning
- Priority suport with SLAs
Enterprise+
Custom Pricing
- Custom Developer seat count
- 100,000 successful models built per month
- 20,000 queried metrics per month
- Unlimited projects
- All features in Enterprise, plus
- PrivateLink
- IP Restrictions
- Run dbt in your own environment (Hybrid Projects)
Pricing details are provided for reference and may differ from the vendor's current plans.
Comments
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