Tower
Tower Raises $6.4m

Effortless data infrastructure for your product

Fully-managed data backend that powers customer-facing features.

Ship product, not infrastructure.

benefits

Why Tower?

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.

Fully-managed data flow orchestration

  • Flows: Choose between Pythonic control flows and Agentic workflows
  • Observability: Gain full flow observability, logs, alerts and metrics
  • Configuration: Manage your settings and secrets in dedicated environments from dev to prod

Open data integration, ETL, and AI Inference

  • Use your favorite ETL Tools: Use community-developed libraries like dltHub, Polars, Apache Data Fusion
  • Unlock the power of agents: Integrate with OpenAI, LangChain, Ollama, llama.cpp and HuggingFace

Lakehouses managed and optimized by Tower

  • Iceberg REST Catalog: Use our managed service or bring your own catalog
  • Table maintenance: Improve performance, clean up wasted storage
  • Ingestion: Stream data into your lakehouse or load it in batches
dbt Core
1import tower
2 
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()

Build using open-source tools

  • Data Transformations: Use dbt Core, dltHub, Polars and DuckDB to build the layers of your lakehouse
  • Catalogs: Lakekeeper, Apache Polaris, Snowflake Open Catalog, Cloudflare R2

Tower vs Competition

How we compare

Tower combines data flow orchestration, flexible compute options, and analytical storage management into a single platform.

GitHub ActionsGitHub Actions
Airflow + Self-Managed ComputeAirflow + Self-Managed Compute
DagsterDagster
TowerTower

Flow Orchestrator

Defining data or control flows

Partial(1)YesYesYes

Flexible Compute Options

Self-hosted Runners for Data Security + Serverless Runners in Tower Cloud

YesPartial(2)Partial(3)Yes

Analytical Storage

Management tools for Lakehouses

NoNoNoYes

Multi-Tenant Platform

Control Plane APIs to run apps and manage users

NoNoPartial(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

Designed for Builders

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

Save months building your platform

Best in class infrastructure
Brought to you by engineers who built Snowflake, Databricks, Google Cloud Dataflow, Puppet, and more
Hardened APIs
Built-in user management, isolated environments, and seamless Python app deployment and execution
Headless Data Stack
Add Tower’s open lakehouse storage and multi-engine capability to your data platform

Flexible Data Plane

Choose between self-hosted runners or serverless infra

Self-Hosted Runners
Process sensitive data in your own cloud account or run local AI inference on data that can’t leave your premises
Serverless Infrastructure
Use our fully-managed service deployed to reliable cloud providers
Observability — Single Pane-of-Glass
Unified logs, metrics, alerts, scheduling and control flows that work across environments

AI-Ready Data Infrastructure

Build the future-proof data infra for your AI

MCP server
Tower MCP server guides your AI Coding Assistants in deploying apps and launching runs
Agent Tools
Turn Tower apps into data agent tools and query your data lakehouse or onboard external data

Testimonials

What our users and partners say

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

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

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

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

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

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

Andy Starzhinsky

VP, a-Gnostics

Power Your Team with Tower

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.