Fully-managed data backend that powers customer-facing features.
Ship product, not infrastructure.
solutions
Orchestrate Python-native pipelines, dbt workflows, notebooks, agents, and tools.
All in one platform.
Run extraction, loading, and transformation pipelines securely and reliably on Tower.
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Develop and run dbt Core models directly on Tower, without relying on additional managed services.
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Power data agents with fresh, reliable business data and ship faster with rapid iteration on Tower.
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Get a Python-native orchestrator of data flows and optionally use a reliable, open lakehouse built on Apache Iceberg and compatible with Snowflake, Spark, and what comes next.
1import tower2 3def main() -> None:4 commands = tower.dbt.parse_command_plan()5 workflow = tower.dbt(6 project_path=project_path,7 profile_payload=tower.dbt.load_profile_from_env(),8 commands=commands,9 )10 workflow.run()Tower vs Competition
Tower combines data flow orchestration, flexible compute options, and analytical storage management into a single platform.
 GitHub Actions |  Airflow + Self-Managed Compute |  Dagster |  Tower | |
|---|---|---|---|---|
Flow Orchestrator Defining data or control flows | Partial(1) | Yes | Yes | Yes |
Flexible Compute Options Self-hosted Runners for Data Security + Serverless Runners in Tower Cloud | Yes | Partial(2) | Partial(3) | Yes |
Analytical Storage Management tools for Lakehouses | No | No | No | Yes |
Multi-Tenant Platform Control Plane APIs to run apps and manage users | No | No | Partial(4) | Yes |
01
GH Action has some orchestration primitives but no flow support
02
Requires use of a Managed Airflow Service
03
Dagster Self-Hosted version requires hosting both Data and Control planes
04
APIs for triggering runs are supported; User management APIs depend on Dagster Self-Hosted vs Dagster Cloud
Multi-tenant Platform
Whether you are a data team building an internal platform, a data + AI consultancy, or a SaaS provider, Tower’s multi-tenant management platform gives you the right building blocks.
Adaptive and Powerful APIs
Flexible Data Plane
AI-Ready Data Infrastructure
Testimonials
Inflow supports customers with sensitive data workloads that must remain on-premises, leveraging a diverse ecosystem of data tools, including Sling Data, dbt, Pentaho, and others, to choose the best fit for each use case. Tower’s self-hosted runners allowed us to consolidate a subset of our customers into a single managed environment, providing a true single pane of glass for observability and a simple, reliable way to deploy and update pipelines.
Itamar Steinberg
CEO, Inflow Systems Ltd
Docker for data? If you go to a docker conference you will hear "portability", "fast onboarding", "lower cognitive load", "implicit access", "microservices", "decentralisation". Who does this for data? Check out dlthub.com/blog/tower
Adrian Brudaru
dltHub Co-founder
I have long suffered at the hands of both the Docker and Python ecosystems. Tower solves both. Plus, it plays nicely with scheduling, orchestration, and open table formats! If you're working with Python, you should try it.
Chris Riccomini
Apache Airflow PMC
dltHub and Tower partner on delivering data movement and transformation. Tower’s data compute infrastructure is tightly integrated with dltHub’s pipelines and notebooks. Users get an end-to-end solution and don’t have to waste time on integrations.
Matthaus Krzykowski
Co-Founder & CEO, dltHub
In the age of ChatGPT, it’s no longer the lack of Python or SQL knowledge that’s holding people back from working with data, it’s the sheer pain of setting up local environments for data access. Tower’s customizable and portable Python runtime is a true game changer for data driven organizations.
Simon Rosenberger
Enterprise AI Lead, Taktile
Migrating to Tower didn’t just streamline our infrastructure — it gave us a competitive edge. With lower costs, faster pipelines, and higher forecast accuracy, a-Gnostics can deliver even more value to customers in energy markets where every percentage point matters.
Andy Starzhinsky
VP, a-Gnostics
tower blog
The Tower team got early access to try dltHub Pro
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Organizations: Tower’s newest feature for centralizing modern data teams
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Tower as an alternative to Modal
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Tower's expansion to the us-east-1 data plane
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Tower's new role-based access is the best way to securely scale your team.
Read more →Get a Python-native orchestrator of data flows and optionally use a reliable, open lakehouse built on Apache Iceberg and compatible with Snowflake, Spark, and what comes next.