Making Big Data Feel Small

DuckDB-powered Cloud Data Warehouse Scaling to Terabytes with Ease

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FINALLY:

A database you don't hate

Why It's Better

Scales Vertically and Horizontally to handle Spikey Workloads

Scales Vertically and Horizontally to handle Spikey Workloads

Reads YOUR data.  (plaintext, json, parquet, iceberg, xls, csv)

Reads YOUR data. (plaintext, json, parquet, iceberg, xls, csv)

Fast, columnar central data storage optimized for analytics

Fast, columnar central data storage optimized for analytics

Run locally, deploy to the cloud for reliability and collaboration. Fits into your workflow

Run locally, deploy to the cloud for reliability and collaboration. Fits into your workflow

Who is it for?

Analytics that works for everyone

Software Engineers

Software Engineers

Who ended up with a big data problem

Data Scientists

Data Scientists

Who ended up having to do data engineering

Data Engineers

Data Engineers

With slow, brittle pipelines

Who is it for?

Analytics that works for everyone

Software Engineers

Software Engineers

Who ended up with a big data problem

Data Scientists

Data Scientists

Who ended up having to do data engineering

Data Engineers

Data Engineers

With slow, brittle pipelines

Use CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse Cases
'For Data Teams' duck illustration'For App Devs' duck illustration
For Data Teams ducks

Data Warehousing

Is your data all over the place? Start making sense of your business by bringing it together for internal business intelligence and analytics. Build pure SQL pipelines, share data and quickly collaborate with your team.

For App Devs ducks

Customer-facing Analytics

Unlike traditional BI, customer-facing analytics is built directly into your product for end users. It delivers near real-time, low-latency insights at scale — think milliseconds, not minutes — and must handle thousands to millions of concurrent queries. MotherDuck's architecture, from per-user tenancy to Wasm support, is designed for the unique requirements of Customer-Facing Analytics to drive increased user engagement directly in your app experience.

How We Scale

Duckling Sizes

MotherDuck’s per-user tenancy model gives each user an isolated
duckling
Tooltip Duckling illustration

A Duckling is a dedicated DuckDB instance for each user, ensuring optimal performance and scalability in data analytics.

(DuckDB instance) in one of three sizes to enable individual, user-level configuration.
MotherDuck Assets illustration
Pulse Instance type illustration

Pulse

Our smallest instance, perfect for ad-hoc analytics tasks

Pulse Duckling
Standard Instance type illustration

Standard

Built to handle common data warehouse workloads including loads and transforms

Standard Duckling
Jumbo Instance type illustration

Jumbo

For larger data warehouse workloads with intense transformations or many BI users

Jumbo Duckling

If you need bigger than Jumbo

Contact Us Duckling

Per-user tenancy and vertical scaling

MotherDuck employs a per-user tenancy and vertical scaling strategy. Users connect to their own MotherDuck Ducklings (DuckDB instances), which are sized (pulse, standard, jumbo) to meet their specific needs. There is also the option for additional Ducklings, through read scaling (explained below), to ensure flexible resource allocation. Ultimately, each Duckling establishes a connection with the central Data Warehouse storage.

Per-user tenancy 
    and vertical scaling

Read Scaling

MotherDuck's read scaling capabilities allow users to connect via a BI Tool to dedicated Ducklings that function as read replicas. These read replicas can be provisioned in various sizes (pulse, standard, or jumbo) to accommodate different needs. Ultimately, these read replicas connect to the Data Warehouse storage, enabling efficient handling of read operations.

Read Scaling

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's photo

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.

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's photo

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.

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's photo

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 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's photo

Kristov Paulus

Founder, Chief Investment Officer

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.

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's photo

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.

DuckDB has a lot of folks in the data community excited—it's a new and unique tool in practitioners' toolboxes and has captured the imaginations of many. MotherDuck's efforts bringing DuckDB to the cloud will broaden the reach of this promising technology.

Tristan Handy's photo

Tristan Handy

CEO & Founder at dbt Labs

DuckDB has a lot of folks in the data community excited—it's a new and unique tool in practitioners' toolboxes and has captured the imaginations of many. MotherDuck's efforts bringing DuckDB to the cloud will broaden the reach of this promising technology.

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's photo

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.

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's photo

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.

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's photo

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's photo

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.

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's photo

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.

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's photo

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 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's photo

Kristov Paulus

Founder, Chief Investment Officer

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.

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's photo

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.

DuckDB has a lot of folks in the data community excited—it's a new and unique tool in practitioners' toolboxes and has captured the imaginations of many. MotherDuck's efforts bringing DuckDB to the cloud will broaden the reach of this promising technology.

Tristan Handy's photo

Tristan Handy

CEO & Founder at dbt Labs

DuckDB has a lot of folks in the data community excited—it's a new and unique tool in practitioners' toolboxes and has captured the imaginations of many. MotherDuck's efforts bringing DuckDB to the cloud will broaden the reach of this promising technology.

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