Comparison

dbt Core vs dlt

No clear leader: dlt (66.1) and dbt Core (64.9) are within the 5-point margin; treat as a tie. The attribute-by-attribute breakdown below, with a source and date on every value, is the honest way to compare them.

Machine formatsJSONMarkdownGraphQLor send Accept: application/json
dbt Core65
dlt66
Score
Vioscale score
dbt Core65 / 100high · 77%
dlt66 / 100low · 49%
Pricing
Free tier
dbt Core
dlt
Model
Price level
dbt Corefree
dltlow
Transparent
dbt Core
dlt
Integrations
Count
dbt Core6
dlt28
Reliability
Status page
dbt Core
dlt
Adoption
Dependent repos
dbt Core553
dlt23
Github stars
dbt Core13,694
Package downloads weekly
dbt Core21,005,917
dlt
Activity
Commits last 30d
dbt Core100
dlt52
Release
Cadence days
dbt Core2
dlt12
History
dbt Core20 items
License
Spdx
Language
Primary
dbt CoreRust

Capabilities

Feature-by-feature on the axes that matter for data engineering tools. “-” means undocumented, not absent.

Core
Tool role
dbt CoreTransformation
dltELT / ingestion
Processing paradigm
dbt CoreBatch
dltBatch + streaming
Connectivity
Connector count
dbt Core6+ named integrations with broader ecosystem
dlt5,000+
CDC / log-based replication
dbt Core-
dlt
Transformation
In-warehouse transformation (push-down)
dbt Core-
dlt
dbt-native orchestration
dbt Core
dlt-
Deployment
Self-hosted / open-source available
dbt Core
dlt
Managed cloud available
dbt Core
dlt
Governance
Data lineage / asset catalog
dbt Core
dlt
Authoring
Python-first authoring
dbt Core-
dlt
Execution
Incremental / partition-aware runs
dbt Core-
dlt
Quality
Built-in data quality / tests
dbt Core
dlt
Scale
Horizontal scale (distributed executor)
dbt Core-
dlt-

What each one is

The product in its own terms, so the numbers below have context.

dbt Core

dbt is a framework that enables data teams to transform data using SQL-based development practices similar to software engineering, with built-in testing, version control, and deployment capabilities. It provides lineage tracking, documentation, and can run locally or in the cloud.

Independently observed

dlt

A hosted service combining the open-source dlt Python library with managed infrastructure, observability, data quality testing, and team collaboration features for building and running data pipelines.

Independently observed

Pricing

List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.

dbt Core

from $100/moHybridFree tier14-day trial

Free Developer tier, $100/seat/month for Starter, custom pricing for Enterprise

  • DeveloperFree
    • Browser-based IDE
    • Multi-factor authentication (MFA)
    • Job scheduling
    • Keep on the latest dbt release
  • Starter$100/seat/month
    • All Developer features
    • dbt Catalog basic
    • dbt Semantic Layer basic
    • dbt Copilot code generation
    • API access
  • EnterpriseContact sales
    • All Starter features
    • dbt Catalog advanced
    • dbt Semantic Layer advanced
    • dbt Copilot
    • dbt Canvas
    • +2 more
  • Enterprise+Contact sales
    • All Enterprise features
    • PrivateLink
    • IP Restrictions
    • Rollback
    • Hybrid projects
as of verify ↗

dlt

from $0.80/moHybridFree tier14-day trial

From $1,190/month with 500 included credits. Free open-source tier. 14-day free trial with $30 credits.

  • dltFree
    • Apache 2.0 open-source license
    • Code-first ingestion library
    • Reliable ingestion and loading
    • Limited verified OSS connectors
    • AI help and community support
    • +2 more
  • dltHub$1,190/month base + $0.80–$1.00/credit for usage beyond 500 credits/month. 5% discount on annual commitment.
    • Everything in dlt, plus:
    • Managed runtime
    • Hosted Marimo notebooks
    • AI Workbench (Claude Code, Codex, Cursor)
    • Data quality metrics and checks
    • +6 more
  • EnterpriseContact sales
    • Custom credits and volume pricing
    • Enterprise security and governance controls
    • Role-based access control (RBAC) and audit logs
    • SLA and tailored support options
    • Custom onboarding and architecture guidance
as of verify ↗

Platform & deployment

Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.

Platforms
Web
dbt Core
dlt
macOS
dbt Core
dlt
Windows
dbt Core
dlt
Linux
dbt Core
dlt
CLI
dbt Core
dlt
Deployment
Cloud / SaaS
dbt Core
dlt
Self-hosted
dbt Core
dlt
Hybrid
dbt Core
dlt

Integrations

What each product connects to. Counts come from the vendor's own integration directory where one exists.

In common (3)
  • OpenAI
  • Snowflake
  • Databricks

dbt Core

6 total - 3 not shared
  • Tableau
  • Fivetran
  • Azure AI
Independently observed

dlt

28 total - 25 not shared
  • Salesforce
  • PostgreSQL
  • HubSpot
  • BigQuery
  • MotherDuck
  • DuckDB
  • SQLite
  • MySQL
  • Amazon S3
  • Google Cloud Storage
  • Microsoft Azure
  • SFTP
  • Parquet
  • Apache Delta
  • Apache Iceberg
  • DuckLake
  • Pydantic Logfire
  • Arize
  • Langfuse
  • LangChain
  • Apache Airflow
  • Dagster
  • AWS Lambda
  • Marimo
  • +1 more
Independently observed

Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.