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.
The cloud DuckDB company
Same DuckDB. Way more duck.
The same DuckDB, running as serverless infrastructure in the cloud: plug AI agents straight in over MCP, share live data, and scale across a million isolated ducklings instead of one laptop.
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Your data, agent-ready
Business context, MCP-native access, and live visuals — everything an agent needs to answer well.
SHOW THE ANSWER
Dives turn live data into interactive visuals people can filter, explore, and share.
ADD BUSINESS CONTEXT
Guides give people and AI agents the context behind your metrics, so the answer is easier to understand and trust.
ASK IN PLAIN ENGLISH
By connecting the MotherDuck MCP to the agent of your choice, the answer to any question inside the data is at your fingertips - no SQL required!
DuckDB in production, without the rebuild
Turn one-off analysis into reliable workflows that run for your team—not just on your laptop.
DEVELOP ON DUCKDB, RUN IT IN THE CLOUD
Explore and test in DuckDB, then run proven work in MotherDuck without rebuilding it in another warehouse.
USE FLIGHTS TO KEEP IT CURRENT
Run scheduled Python jobs inside MotherDuck, so production data stays current without manual reruns.
SCALE AS DEMAND GROWS
Use 5 different Duckling sizes and read scaling as more data and queries arrive.
Bring more people into the analysis
MotherDuck gives colleagues, leadership, and customers a way to work from your DuckDB data—not a chain of exported files.
SHARE LIVE DATA
Create database shares for the people who need them. Keep everyone connected to current data instead of passing around exports.
ISOLATED COMPUTE FOR EVERY USER
With isolated DuckDB instances, your whole team can work concurrently, without getting in one another’s way.
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.
Architecture
Managed DuckDB-in-the-cloud
Ecosystem
Modern Duck Stack
CLOUD DATA WAREHOUSE
Sources
AI Agents
Ingestion
Business Intelligence
Reverse ETL
Transformation
Data Science & AI
Case Studies
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.
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.
FAQS
MotherDuck is the cloud DuckDB company: the same DuckDB you already know, run as serverless cloud infrastructure. You keep the engine and your SQL, and gain scale beyond one machine, live shared data, and the pieces to build AI on top—agent access over MCP, Guides, Dives, and Flights.
Yes. MotherDuck connects trusted DuckDB data to MCP-compatible agents, adds business context with Guides so agents interpret metrics consistently, and turns answers into live, interactive visuals with Dives.
Through the MotherDuck MCP server. Connect the agent of your choice and it can answer questions directly from your live data—no SQL required.
Guides add shared business context to data questions. They help people and AI agents interpret metrics consistently instead of relying on an undocumented definition of the data.
Dives are live, interactive data visualizations built with SQL or an AI agent. People can filter, drill into, share, and embed the results while staying connected to live data.
Flights are scheduled Python data pipelines that run inside MotherDuck. They turn one-off ingestion or transformation work into repeatable jobs that keep data current.
DuckDB is an open-source analytical database commonly used locally and in-process. MotherDuck runs that same engine as serverless cloud infrastructure—adding shared live data, scheduled workflows, isolated compute for concurrent users, agent access over MCP, and datasets larger than a local machine can handle.
Yes. MotherDuck is the managed cloud environment built on DuckDB. Keep developing locally, then run shared, production, and AI workloads in the cloud when the work grows beyond one machine.
MotherDuck is built on DuckDB, so existing SQL, scripts, and supported client libraries remain the starting point. See the setup documentation for exact connection and client details.
MotherDuck provides cloud storage and compute beyond the resources available on a laptop, with five Duckling sizes and read scaling as data and queries grow. This lets you query larger datasets without rebuilding the analysis in another warehouse.
Yes. MotherDuck can query data in S3, GCS, and MotherDuck-managed storage. See the integration documentation for supported formats and setup details.
Move when the work outgrows one machine: sharing results and live data with your team, giving AI agents governed access to your data, keeping data current with scheduled jobs, querying larger datasets, or supporting concurrent users.
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.
