Serverless DuckDB
Run DuckDB SQL analytics in a serverless cloud data warehouse. Dual execution runs query stages on your laptop, in the cloud, or across both, and zero-copy shares let teammates query the same data.
Serverless Data Warehouse Built on DuckDB
Analytics infrastructure for data teams, app developers & AI agents.
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For App Devs
Ship customer-facing analytics with a serverless DuckDB database. Use per-customer compute, Postgres compatibility, and embedded Dives to make your application fly!
For Data Teams
Run DuckDB in the cloud for fast, efficient analytics. Ingest and transfrom your data with Flights, give context to agents with Guides, and build visuals with Dives. Source controlled end-to-end.
What Makes MotherDuck Unique?
The Old World
Bin-packed, high latency workloadsAnalytics are too cumbersome
With all your users in one big, shared box, they’re constantly competing for resources and compute, making load times unbearable...why are we doing this?
Scaling is resource-intensive
With a traditional DWH, power users run into latency issues as processing scales. Deciding which users to bin-pack and which to isolate on their own instance is cumbersome and sloooooooow.
No visibility of user-level usage
It’s impossible to understand who is driving the lion’s share of usage and how to prevent your database and the applications built on top from grinding to a halt. The struggle is real - but there’s finally a better way.
The MotherDuck World
Data warehouse without the overheadSimple, straightforward analytics
MotherDuck is the first analytics data warehouse that offers cloud scale and individualized, user-level tenancy. Managing user-level compute limits and cost attribution without cumbersome upfront configuration hasn’t been possible until now.
The first truly personal data warehouse
Each user automatically gets their own compute instance “duckling” so end users can move quickly and freely from question to insight. Best of all: No more waiting around for queries to process because someone else is using too much compute!
User-level CPU Visibility by design
Built-in user-level CPU visibility ensures a consistent, smooth experience for all your users. Cost attribution at the user-level helps you predict and proactively optimize costs without additional overhead - say goodbye to surprise bills when usage scales up.
THE AI NATIVE CLOUD DATABASE
Architecture
Managed DuckDB-in-the-cloud
Features
MCP for AI agents
Connect Claude, ChatGPT, Cursor, or any MCP-compatible agent to MotherDuck. Natural-language questions come back as accurate, traceable SQL, running in sandboxed compute.
Share business context
Guides give AI agents shared business context on every query, so natural-language answers stay accurate for the people who know the business.
Live data visualizations
Dives are live, interactive visualizations built by an AI agent or with SQL — filter and drill down on live data, share them, or embed them in your app.
Scheduled data pipelines
Flights are scheduled Python data pipelines that run inside MotherDuck. Describe a source and your agent writes, deploys, and schedules the ingestion job.
Isolated compute
Hypertenancy gives each user, customer, or AI agent an isolated DuckDB instance — high concurrency with no shared clusters or noisy neighbors, plus up to 16 read-scaling replicas.
Ecosystem
Modern Duck Stack
CLOUD DATA WAREHOUSE
Sources
AI Agents
Ingestion
Business Intelligence
Reverse ETL
Transformation
Data Science & AI
Case Studies
Every meeting now is shifted from trying to find answers to what to do about them. Users are able to make a Dive or chat with MotherDuck through Claude, find new design issues, and ask: what should we do about it?
Ben Holtzman
VP of Data at AheadComputing
Every meeting now is shifted from trying to find answers to what to do about them. Users are able to make a Dive or chat with MotherDuck through Claude, find new design issues, and ask: what should we do about it?
We now have a doctor vibe-coding artifacts and tools that can talk to all the data that the company has, run processes, and then actually go and affect them directly.
Greg Inman
CTO at Zero Health
We now have a doctor vibe-coding artifacts and tools that can talk to all the data that the company has, run processes, and then actually go and affect them directly.
MotherDuck is insanely performant, and there’s no infrastructure to manage. The cost of experimentation is incredibly low — which means we can afford to ask more questions and build more features, faster.
Kristov Paulus
Founder, Chief Investment Officer at Kultura Capital
MotherDuck is insanely performant, and there’s no infrastructure to manage. The cost of experimentation is incredibly low — which means we can afford to ask more questions and build more features, faster.
We used to do analytics in a MySQL database with all of our daily device, telemetry, and image processing data. There was no way to scale that further using MySQL. With MotherDuck, we’re finally starting to find patterns in our data to help customers grow produce more effectively.
Rob Teeuwen
Data Scientist at Gardyn
We used to do analytics in a MySQL database with all of our daily device, telemetry, and image processing data. There was no way to scale that further using MySQL. With MotherDuck, we’re finally starting to find patterns in our data to help customers grow produce more effectively.
Instant SQL in MotherDuck will save me the misery of having to try and wrangle SQL in my BI tool where iteration speed can be very slow. This lets me get the data right earlier in the process and with faster feedback than waiting for a chart to render, or having to clear an analytics cache.
Mike McClannahan
CTO, DashFuel
Instant SQL in MotherDuck will save me the misery of having to try and wrangle SQL in my BI tool where iteration speed can be very slow. This lets me get the data right earlier in the process and with faster feedback than waiting for a chart to render, or having to clear an analytics cache.
Bringing MotherDuck into our data stack has been a game changer. We're reducing friction and supercharging our dev and ops experience by leveraging the DuckDB interoperability across local and cloud.
Ravi Chandra
CTO at Dexibit
Bringing MotherDuck into our data stack has been a game changer. We're reducing friction and supercharging our dev and ops experience by leveraging the DuckDB interoperability across local and cloud.
Moving to MotherDuck, a billed by-the-second cloud offering is a no-brainer for us, considering the elegance and efficiency of a single node system compared to traditional OLAP solutions.
Nico Ritschel
Director of Engineering at atm.com
Moving to MotherDuck, a billed by-the-second cloud offering is a no-brainer for us, considering the elegance and efficiency of a single node system compared to traditional OLAP solutions.
MotherDuck with DuckDB was by far the fastest of the OLAP platforms we evaluated - both in the cloud and run on our developer's machines - bridging price and performance and greatly increasing productivity.
Jim O’Neill
CTO and Co-founder at FinQore
MotherDuck with DuckDB was by far the fastest of the OLAP platforms we evaluated - both in the cloud and run on our developer's machines - bridging price and performance and greatly increasing productivity.
I just onboarded some non-technical users to MotherDuck, and I can’t imagine having done so in a different system with this level of ease and lack of intimidation. Between the ‘Filter’ button, Column Explorer, and the FROM syntax - they feel empowered to answer many of their own questions! 🙂
Sahil Gupta
Senior Data Engineer at dosomething.org
I just onboarded some non-technical users to MotherDuck, and I can’t imagine having done so in a different system with this level of ease and lack of intimidation. Between the ‘Filter’ button, Column Explorer, and the FROM syntax - they feel empowered to answer many of their own questions! 🙂
MotherDuck proving once again they are not constrained by what is easy or common. Instant SQL will not only enable complex query construction for those who find the task daunting (everyone?), it'll help past me communicate with future me.
SJ Browne
Software Engineer at DashFuel
MotherDuck proving once again they are not constrained by what is easy or common. Instant SQL will not only enable complex query construction for those who find the task daunting (everyone?), it'll help past me communicate with future me.
On top of compute-heavy warehouses, agent-driven queries would create a serious cost problem. MotherDuck's architecture is an excellent fit for the kind of exploration and unpredictable queries that agents need to be useful.
Pablo Ferrari
Director of Data Engineering at Together AI
On top of compute-heavy warehouses, agent-driven queries would create a serious cost problem. MotherDuck's architecture is an excellent fit for the kind of exploration and unpredictable queries that agents need to be useful.
FAQS
Hypertenancy gives each user, customer, or AI agent an isolated DuckDB instance called a Duckling, so workloads do not compete for shared compute.
The MotherDuck MCP Server lets AI agents inspect catalogs and run SQL, read Guides, create Dives, and manage Flights.
MotherDuck shares databases through read-only share objects. A provider creates a zero-copy share, and consumers attach it to their workspace and query it without exporting files or making a second copy.
Yes, MotherDuck can query data stored in S3 and other S3-compatible object storage. See our authentication and querying guides.
You can connect with DuckDB clients such as Golang and Python, or use the MotherDuck UI and other supported interfaces. See our connection guides.
MotherDuck supports BI and data visualization tools such as Omni, Hex, Tableau, and Power BI. See the MotherDuck ecosystem for more integrations.
dbt users can take advantage of the DuckDB dbt adapter, which works with MotherDuck. See our dbt guide.
Get in Touch
We’d love to learn more about what you’re building. A Product Expert will fly right back to you with resources to help you take flight.
