Training Example: MotherDuck – Review the Data, Give Your Score & Compare to the Real AI Evaluation

[H1] Infrastructure for Answers
The cloud data warehouse built for answers, in SQL or natural language. Fast, serverless analytics powered by DuckDB–from production apps to internal insights.Try 7 Days FreeBook a Demo
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[H2] "DuckDB In Action"
Book for Free
Get the complete book for free in your inbox!Data Warehouse + AIData Warehouse + AIData Warehouse + AIData Warehouse + AIData Warehouse + AIData Warehouse + AIData Warehouse + AIData Warehouse + AI
[H2] Data Warehouse + AI
[H3] Hypertenancy Data Warehouse
A cloud analytical database that scales per-user compute nodes independently, serving sub-second latency without resource contention.Learn more
[IMG: Diagram of AI agents and human users simultaneously querying a shared MotherDuck data warehouse]
[H3] MotherDuck MCP Server
Turn natural language questions into accurate, traceable SQL queries with fully sandboxed compute.Learn more
[IMG: Illustration of MotherDuck MCP tools including list_databases, search_catalog, ask_docs_question, and query]
[H2] Who is it for?
Cloud analytics and data warehouse solutions for every team
[H3] Software Engineers
Who ended up with a big data problem
[H3] Data Scientists
Who ended up having to do data engineering
[H3] Data Engineers
With slow, brittle pipelines
[H2] Who is it for?
Cloud analytics and data warehouse solutions for every team
[H3] Software Engineers
Who ended up with a big data problem
[H3] Data Scientists
Who ended up having to do data engineering
[H3] Data Engineers
With slow, brittle pipelinesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse CasesUse Cases
[H2] Use Cases
[H3] Data Warehousing
Is your data all over the place? Modern cloud data warehouse tools bring it together for business intelligence and SQL analytics. Build data pipelines, share data, and collaborate with your team.How it WorksCase Studies
[H3] Customer-facing Analytics
Unlike traditional BI, customer-facing analytics is built directly into your product for end users. This embedded analytics solution delivers real-time, low-latency insights at scale — think milliseconds, not minutes — powered by a columnar database that handles thousands to millions of concurrent queries. MotherDuck's architecture, from Hypertenancy to Wasm support, is designed for Customer-Facing Analytics that drives user engagement directly in your app.How it WorksCase Studies
[H2] How We Scale
[H3] Duckling Sizes
MotherDuck’s per-user tenancy model gives each user an isolated ducklingA Duckling is a dedicated DuckDB instance for each user, ensuring optimal performance and scalability in data analytics. (DuckDB instance) in one of five sizes to enable individual, user-level configuration.
[IMG: Pulse Duckling]
[IMG: Pulse Instance type illustration]
PulseOur smallest instance, perfect for ad-hoc analytics tasks
[IMG: Standard Duckling]
[IMG: Standard Instance type illustration]
StandardBuilt to handle common data warehouse workloads, including loads and transforms
[IMG: Jumbo Duckling]
[IMG: Jumbo Instance type illustration]
JumboFor larger data warehouse workloads with many transformations or complex aggregations
[IMG: Mega Duckling]
[IMG: Mega Instance type illustration]
MegaAn extremely large instance for when you need complex transformations done quickly
[IMG: Giga Duckling]
[IMG: Giga Instance type illustration]
GigaLargest instances enable the toughest transformations to run fasterTake a closer look atDUCKLING SIZES
[H3] Hypertenancy and vertical scaling
MotherDuck's cloud data warehouse employs a Hypertenancy and vertical scaling strategy. Users connect to their own MotherDuck Ducklings (DuckDB instances), which are sized (pulse, standard, jumbo, mega, giga) 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.Learn more
[IMG: Diagram showing multiple users each connected to their own dedicated Duckling (sized Jumbo, Standard, or Pulse) that routes queries to a shared MotherDuck data warehouse]
[H3] 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, jumbo, mega or giga) to accommodate different needs. Ultimately, these read replicas connect to the Data Warehouse storage, enabling efficient handling of read operations.
[IMG: Diagram showing multiple users connecting through a BI tool to dedicated read replica Ducklings (Read Replica A, B, C) that all connect to a shared MotherDuck data warehouse]
[H2] Ecosystem
Modern Duck Stack
[H3] CLOUD
DATA WAREHOUSE
[H3] Sources
[H3] AI Agents
[H3] Ingestion
MORE INFO
[H3] Business Intelligence
MORE INFO
[H3] Reverse ETL
MORE INFO
[H3] Transformation
MORE INFO
[H3] Data Science & AI
MORE INFO
[H3] Orchestration
MORE INFO
[H3] Data Quality
MORE INFO
[H2] Join the flock
CHAT WITH US ON SLACK
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[H2] SUBSCRIBE
[H3] Subscribe to our newsletter

[H1] Meet the Flockers
Discover the power of partnership with motherduck’s extensive ecosystem
[H2] Technology Partners
AllIngestionReverse ETLBusiness IntelligenceData Science & AIOrchestrationData QualityDev ToolsTransformationData Apps
[IMG: Airbyte]
INGESTION
[H3] Airbyte
Airbyte is an open-source data integration platform that enables the seamless transfer of data from various sources to data warehouses, lakes, and other destinations. It supports a vast range of connectors and provides an intuitive interface for managing data pipelines, ensuring data consistency and reliability. Airbyte offers both a community edition and a cloud service, allowing flexibility in deployment and scalability.
## Airbyte + MotherDuck
Airbyte integrates with MotherDuck by facilitating the extraction, transformation, and loading (ETL) of data from numerous sources directly into the MotherDuck cloud data warehouse. Utilizing Airbyte's extensive library of connectors, users can automate and streamline the process of moving data into MotherDuck, ensuring that their cloud data warehouse remains up-to-date and easily accessible for analysis.DocsBlog
[IMG: AirFlow]
ORCHESTRATION
[H3] AirFlow
Apache Airflow is an open-source platform designed to programmatically author, schedule, and monitor workflows. It allows users to define tasks and their dependencies as code, enabling dynamic pipeline generation and complex data orchestration. Airflow supports a rich set of integrations and extensibility through custom plugins and operators.
## Apache Airflow + MotherDuck
Apache Airflow integrates with MotherDuck by leveraging custom operators to connect to the MotherDuck cloud data warehouse. This allows users to execute SQL queries and manage data workflows directly within the Airflow environment, utilizing DuckDB's efficient analytical capabilities in a cloud-native setting.Docs
[IMG: Anthropic]
DATA SCIENCE & AI
[H3] Anthropic
Anthropic is an AI safety company and the creator of Claude, a family of large language models designed to be helpful, harmless, and honest. Claude is used across industries for tasks ranging from analysis and coding to content generation and research, and is available through claude.ai, the Claude API, and a growing ecosystem of connectors and integrations.
## ANTHROPIC + MOTHERDUCK
MotherDuck is available as a connector on Claude.ai, allowing users to connect their MotherDuck data warehouse directly to Claude. With this integration, users can explore and analyze their data using natural language — no SQL skills required. Claude acts as an AI-powered data analyst, iterating through exploration, validation, and visualization to surface useful answers from your MotherDuck databases.
The connector provides safe, read-only access and works with messy, real-world data without requiring a semantic model or pre-configuration. Whether you're listing tables, querying top customers by revenue, or searching your data catalog for churn-related datasets, Claude and MotherDuck together make data accessible to every team member.Docs
[IMG: Artie]
INGESTION
[H3] Artie
Artie is the modern data infrastructure layer for the AI era — a fully managed CDC streaming platform that keeps production data continuously in sync with your warehouse.
As companies activate their warehouses for real-time AI workloads, analytics, and customer-facing data products, they're standardizing on infrastructure that's fast, reliable, and built for scale.
Artie automates the entire ingestion lifecycle — change capture, merges, backfills, and observability — with zero engineering maintenance and deploys in minutes.
Leaders like Substack, ClickUp, and Alloy use Artie not just to solve today's pipeline issues, but to future-proof their data stack as their AI strategy accelerates.
## Artie + MotherDuck
With Artie's MotherDuck integration, you can stream data from sources like PostgreSQL, SQL Server, and MySQL into your MotherDuck data warehouse–perfect for running analytical queries on your application data or integrating with third-party data in a single warehouse.Docs
[IMG: Ascend]
TRANSFORMATIONINGESTION
[H3] Ascend
Ascend.io is an intelligent data pipeline automation platform that streamlines the creation, operation, and maintenance of data workflows. It provides end-to-end automation, ensuring data engineers can build scalable data pipelines with minimal effort. Ascend.io leverages a unified data ingestion, transformation, and orchestration layer to simplify complex data engineering tasks.
## Ascend.io + MotherDuck
Ascend.io integrates with MotherDuck by enabling seamless data pipeline automation that connects directly to MotherDuck's cloud data warehouse. This integration allows users to effortlessly ingest, transform, and orchestrate data within MotherDuck, leveraging DuckDB’s high-performance querying capabilities to optimize data processing and analytics workflows.Blog
[IMG: Astrato Analytics]
[H3] Astrato Analytics
Astrato is a warehouse-native BI platform that lets teams build pixel-perfect, interactive dashboards directly on their cloud data. Purpose-built for customer-facing and embedded analytics, Astrato combines a semantic layer, white-labelling, and automated reporting so BI teams can ship governed analytics to external stakeholders without writing code.
## Astrato + MotherDuck
Astrato integrates with MotherDuck to deliver production-grade embedded analytics using an intuitive drag-and-drop builder. Teams create pixel-perfect, white-labelled dashboards that query MotherDuck in real time – zero data extracts, zero infrastructure to manage.
The integration is built for teams that want to monetize their data: building customer-facing analytics products, offering premium data experiences, or embedding interactive reporting directly into their applications. Astrato queries MotherDuck live, keeping governance intact while MotherDuck's per-second billing ensures costs stay predictable as you scale.
Key capabilities: pixel-perfect dashboarding, multi-tenant security with SSO pass-through, automated scheduled reporting (branded PDF, Excel, PowerPoint), and iframe embedding — all without code.
[IMG: Astronomer]
ORCHESTRATION
[H3] Astronomer
Astronomer Airflow is a managed service for Apache Airflow, providing robust orchestration and scheduling of complex data workflows. It offers scalability, reliability, and ease of use with features such as auto-scaling, monitoring, and a user-friendly interface. Designed for data engineers and analysts, it simplifies the deployment and management of Airflow environments, ensuring seamless data pipeline execution.
## Astronomer Airflow + MotherDuck
Astronomer Airflow can be integrated with MotherDuck by orchestrating data workflows that involve querying, analyzing, and transforming data within the MotherDuck cloud data warehouse. Using Airflow operators, users can automate and schedule SQL queries and data processing tasks directly on MotherDuck, facilitating efficient data pipeline management and execution.BlogDocs
[IMG: Bruin]
ORCHESTRATIONINGESTIONDATA QUALITY
[H3] Bruin
Bruin is an end-to-end data platform that brings together data ingestion, transformation using SQL and Python, data quality and governance.
- Ingestion: You can ingest data from a variety of sources such as databases, marketing platforms, CRM tools, and more.
- Transformation: You can transform your data inside the data warehouse using SQL and Python. Built-in materialization strategies, incremental processing, Jinja templating, and more.
- Data Quality: Bruin allows you to ensure your data is accurate on a regular basis, whether it comes in externally or you built it. You can run column-level and custom quality checks, track the distribution of your data, run cross-table quality checks, and get alerts automatically.
- Data Governance: Bruin allows scaling your data infrastructure via built-in governance reports, glossaries, metadata policies, cost reports, and more. You can run all Bruin checks in your CI/CD pipelines, ensuring your data pipelines always fit what you expect. DocsDocs
[IMG: Bytewax]
INGESTIONTRANSFORMATION
[H3] Bytewax
Open source framework and distributed stream processing engine. Build streaming data pipelines and real-time apps with everything you need: recovery, scalability, windowing, aggregations, and connectors.BlogVideo
[IMG: Census]
REVERSE ETL
[H3] Census
Census is a reverse ETL tool that allows businesses to sync data from their data warehouse directly into the apps they use, such as CRMs, marketing platforms, and other SaaS tools. It helps ensure that all teams have access to the most up-to-date, actionable data by automating the data sync process. Census supports a wide range of data warehouses and enables data-driven workflows without requiring manual data exports or custom integrations.
## Census + MotherDuck
Census integrates with MotherDuck by using MotherDuck's cloud data warehouse capabilities built on DuckDB. This integration allows users to easily sync and transform data stored in MotherDuck to various business applications and SaaS tools. Consequently, data teams can leverage MotherDuck's robust querying and analytics features while ensuring that actionable insights are seamlessly propagated to operational tools via Census.Blog
[IMG: CloudQuery]
INGESTION
[H3] CloudQuery
CloudQuery is an open-source data integration platform that enables the transformation of cloud assets into SQL-accessible databases. It helps organizations extract, transform, and load (ETL) data from various cloud providers into a format suitable for analysis and monitoring. CloudQuery supports a wide range of cloud services and offers a flexible configuration for custom data pipelines.
## CloudQuery + MotherDuck
CloudQuery integrates with MotherDuck by allowing users to load and transform data from multiple cloud sources directly into the MotherDuck cloud data warehouse. This integration leverages CloudQuery’s ETL capabilities to efficiently funnel data into MotherDuck, making it accessible for advanced analytics and querying through DuckDB's SQL engine.Blog
[IMG: Cube]
BUSINESS INTELLIGENCE
[H3] Cube
Cube is an API-first analytics platform that enables data engineers and developers to build data applications. It provides a semantic layer to unify data sources, caching, and pre-aggregation for fast query performance. Cube supports various data sources and visualization tools, making it a versatile solution for creating and managing analytical data workflows.
## Cube + MotherDuck
Cube integrates with MotherDuck by leveraging its DuckDB-based architecture to efficiently query and analyze data stored in the MotherDuck cloud data warehouse. This integration enables Cube to utilize MotherDuck's high-performance SQL engine, providing fast and seamless access to large datasets for building robust data applications.BlogVideoDocs
[IMG: Dagster]
ORCHESTRATIONINGESTION
[H3] Dagster
Dagster is an open-source data orchestrator designed for the development, production, and observation of data assets. It helps data teams to define, schedule, and monitor complex data workflows, ensuring data reliability and quality. Dagster provides a rich development experience with type-safe pipelines, integrated testing, and seamless collaboration.
## Dagster + MotherDuck
Dagster integrates with MotherDuck by leveraging DuckDB's capabilities within its orchestration workflows. This integration allows data engineers and analysts to run efficient, in-memory SQL queries on data stored in MotherDuck, enabling seamless data processing and analytics within Dagster's pipeline framework. The combined use of Dagster and MotherDuck enhances the ability to manage and analyze data workflows with high performance and flexibility.
## Customer Success Stories
Teams orchestrate production data pipelines with Dagster and MotherDuck:
- **[Gardyn](/case-studies/gardyn/)** uses Dagster Cloud for data ingestion, reducing daily pipeline execution from 24+ hours to under an hour.
- **[UDisc](/case-studies/udisc-motherduck-sports-management/)** relies on Dagster for data orchestration, delivering analytics to millions of disc golf enthusiasts.
- **[Trunkrs](/case-studies/trunkrs-same-day-delivery-motherduck-from-redshift/)** orchestrates their same-day delivery data workflows with Dagster and MotherDuck.DocsBlog
[IMG: Datagrip]
DEV TOOLS
[H3] Datagrip
DataGrip is a powerful database management tool developed by JetBrains, designed for SQL developers. It provides intelligent query completion, robust code analysis, and refactoring capabilities, supporting various databases like MySQL, PostgreSQL, and Oracle. DataGrip offers a unified interface, enabling users to manage and explore databases efficiently.
## DataGrip + MotherDuck
DataGrip integrates with MotherDuck by leveraging its JDBC connector to connect to the MotherDuck cloud data warehouse. This enables users to execute queries, manage schemas, and analyze data stored in MotherDuck directly from the DataGrip interface.DocsDocs
[IMG: DataLab]
DATA SCIENCE & AI
[H3] DataLab
DataLab is a collaborative data science platform designed for data analysts and scientists to explore, analyze, and visualize data in a unified workspace. It offers robust tools for data preparation, machine learning, and interactive dashboards, enabling teams to work seamlessly on shared projects. DataLab supports various data sources and integrates with popular programming languages like Python and R, streamlining the data workflow from ingestion to insights.
## DataLab + MotherDuck
DataLab integrates with MotherDuck by allowing users to connect directly to MotherDuck's cloud data warehouse, leveraging DuckDB's efficient querying capabilities. This integration enables DataLab users to perform high-performance data analysis and visualization on large datasets stored in MotherDuck, enhancing their ability to derive actionable insights quickly.Docs
[IMG: Datawisp]
BUSINESS INTELLIGENCE
[H3] Datawisp
Datawisp is a no code analytics platform that lets anyone analyze data and discover insights regardless of their technical knowledge. Its node-based interface allows users to combine different “blocks” to transform data, much like a developer would with code. Each block performs a different operation, such as filtering, sorting, or creating a chart, and linking even 3 or 4 of these blocks can transform and analyze data in powerful ways.
Datawisp also features an AI-powered assistant, named Wispy, that takes natural language input from the user and automatically creates charts, tables, and more. Worksheets created by Wispy can be used as-is or can be subsequently edited manually by anyone with some knowledge of how blocks work.
Datawisp runs in a browser and lets users collaborate in real time and share their work with both internal and external audiences.Docs
[IMG: dbt Core]
TRANSFORMATION
[H3] dbt Core
dbt (data build tool) is a command-line tool that enables data anal

[H1] Blazing fast analytics, ducking simple pricing
Plans that fit customer-facing analytics and internal data warehousing use cases.
[IMG: Lite plan]
LiteStarting
from$0For solo practitioners and hobbyists leaving the nestStart FreeIncludes:Up to 3 internal active users and 2 service accounts10 GB free storage10 hrs Pulse compute per month includedPulse instances onlyCommunity support
[IMG: Business plan]
Business$250PER ORG
/ MONTH + USAGEEverything you need for production analyticsTry 7 days FREEScale up to production with:Up to 10 internal active users and unlimited service accounts5 instance types and read-scaling replicas90-day snapshot retentionQuery historySupport from MotherDuck experts99.9% availability SLASEE INSTANCE TYPES
[IMG: Enterprise plan]
EnterpriseCustomCustomized plans for large-scale deploymentsContact UsEverything in Business, plus:Unlimited internal active users and service accountsFixed-cost capacity pricingAWS PrivateLink connectivityHIPAA BAASEE INSTANCE TYPESLooking for an annual plan?
Get in touch 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 RitschelDirector of Engineering @ atm.com
[IMG: Nico Ritschel]
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 PaulusFounder, CIO @ Kultura Capital
[IMG: Kristov Paulus]
[H2] Compare Plans
RegionUSA (N. Virginia): us-east-1MotherDuck Data WarehouseData WarehouseMotherDuck Data WarehouseData WarehouseInternal UsersInternal users in your organization.Up to 3 active usersUp to 10 active usersUnlimitedEnd UsersEnd users of applications built on MotherDuck.UnlimitedUnlimitedUnlimitedService AccountsService accounts for programmatic access to your organization. Learn more about Service AccountsUp to 2UnlimitedUnlimitedPlatform AccessAccess to MotherDuck for your team. Learn more about Platform Access$0 per org / month$250 per org / monthCustomMotherDuck MCPQuery your data in natural language. Learn more about MotherDuck MCPStorageCost effective, low latency storage. Learn more about Storage$0.04 per GB / month$0.04 per GB / monthCustomCompute Instances:PulseFor lightweight, bursty workloads. Billed per compute unit (CU) second. Learn more about Pulse compute pricing(Billed per second)$0.60 per hour$0.60 per hourCustomStandardFor everyday tasks and balanced performance. Billed per second. Learn more about Standard compute pricing(Billed per second)$2.40 per hourCustomJumboFor predictable performance on heavy workloads. Billed per second. Learn more about Jumbo compute pricing(Billed per second)$4.80 per hourCustomMegaFor demanding jobs at an even larger scale. Billed per second. Learn more about Mega compute pricing(Billed per second)$12.00 per hourCustomGigaFor the largest and toughest workloads. Billed per second. Learn more about Giga compute pricing(Billed per second)$36.00 per hourCustomRead ScalingEnable up to 16 read-scaling replicas, each backed by its own instance, for BI dashboards and read-only use cases. Learn more about Read ScalingQuery HistoryA consolidated view of all queries run across your organization. Learn more about Query HistoryAI FunctionsSingle call and bulk AI functions, including prompt() and embedding(). Learn more about AI Functions$1.00 per AI Unit$1.00 per AI UnitDual ExecutionIncredibly efficient queries, shared across local and cloud compute. Learn more about Dual ExecutionManaged DuckLakeThe simplest data lake, fully managed. Learn more about Managed DuckLakeSnapshot RetentionQueryable database snapshots for history and backup. Learn more about Snapshot RetentionUp to 1 dayUp to 90 daysUp to 90 daysWorkflow and CollaborationWorkflowWorkflow and CollaborationWorkflowInstant SQLBuild and debug faster with
zero-latency query results
Learn more about Instant SQLFixItResolve SQL errors with in-line fixes
Learn more about FixItColumn ExplorerInstantly visualize the columns
of your tables and result sets.
Learn more about Column ExplorerDatabase SharingShare zero-copy snapshots
for easier collaboration
Learn more about Database SharingDivesReal-time, shareable visualizations. Learn more about DivesEmbedded DivesEmbed interactive Dives in your own applications. Learn more about Embedded DivesSecurity And ComplianceSecurity &ComplianceSecurity And ComplianceSecurity &ComplianceSingle Sign-OnSingle Sign-On (SSO) via standards-based SAML & OIDC (Okta, Entra ID, Google Workspace). Learn more about Single Sign-OnSCIMAutomate user provisioning and deprovisioning via your identity provider. Learn more about SCIMSOC 2 Type IIFull compliance with SOC 2 Type II.
Learn more about SOC 2 Type II complianceGDPR ComplianceGeneral Data Protection Regulation (GDPR) compliant. Learn more about GDPR ComplianceAWS Private LinkSecure, private connectivity through the AWS networkHIPAA BAAAvailable on request. Contact us for more detailsSupportSupportHuman-First SupportSupportHelpful support engineers in the US + EU. Learn more about Human-First SupportCommunityAccess to MotherDuck expertsStandardAccess to MotherDuck experts with a response SLAPriorityFaster access to MotherDuck experts with an expedited response SLAIn-App Expert ChatIn-App Expert ChatChat with product experts directly
from the MotherDuck UIAvailability SLAGuaranteed uptime for your production workloads. Learn more about Availability SLA99.9%Custom
[H2] Serverless Instances
MotherDuck’s Hypertenancy model gives each internal or end user an isolated compute instance to enable independent scaling.
[IMG: Pulse Instance type illustration]
[H3] Pulse
Our smallest instance, perfect for ad-hoc analytics tasksCommonly used when...Doing ad-hoc analytics tasks with datasets in MotherDuckBuilding read-only workloads with high volumes of concurrent users like customer-facing analytics applicationsA larger, dedicated instance is overkill for the task at handIncluded Plans: Lite Business Enterprise
[IMG: Standard Instance type illustration]
[H3] Standard
Built to handle common data warehouse workloads, including loads and transformsCommonly used when...Performing typical data engineering tasks like data ingest and dbt transformationsRunning dbt jobs that have multiple transformations in parallelBuilding out standard data pipelines before moving to production and scaling upIncluded Plans: Lite Business Enterprise
[IMG: Jumbo Instance type illustration]
[H3] Jumbo
For larger data warehouse workloads with many transformations or complex aggregationsCommonly used when...Query complexity, data volume, and the number of transformations are too high for the Standard instancePerforming complex joins and aggregations on growing datasets using event stream data or nested JSON with changing schemasRunning faster with your workloadsIncluded Plans: Lite Business EnterpriseAnd for even heavier workloads...
[IMG: Mega Instance type illustration]
[H3] Mega
An extremely large instance for when you need complex transformations done quicklyCommonly used when...Queries are too complex or data volumes too high for Jumbo instances to handle in crunch timeRunning a weekly job that rebuilds all of your tables and it has to run in minutes, not hoursOne customer has 10x the amount of data as others and you want to deliver same speedIncluded Plans: Lite Business Enterprise
[IMG: Giga Instance type illustration]
[H3] Giga
Largest instances enable the toughest transformations to run fasterCommonly used when...Your data workload is so complex that nothing else will workRunning a one-time job to go back and restate revenue for the last 10 years at a large companyYou need a growth path beyond Mega for when your data volume and complexity grows 10xIncluded Plans: Lite Business Enterprise
[H2] flock together with 40+ integration partners
[IMG: Hex logo]
[IMG: Dbt logo]
[IMG: Omni logo]
[IMG: Airflow logo]
[IMG: Fivetran logo]
[IMG: Superset logo]
[IMG: Tableau logo]
[IMG: Airbyte logo]
[IMG: PowerBI logo]
[IMG: Dagster logo]
EXPLORE ECOSYSTEM
[H2] Built for humans, powered by ducks
MotherDuck’s strategic partnership with DuckDB Labs brings the fast improving efficiencies of DuckDB’s query engine from local machines to the cloud as a managed service. Working closely with the DuckDB Labs team has helped us co-create a shared vision for the future of blazing fast analytics. Together, we are committed to cutting-edge innovation in service of ergonomic, radically streamlined analytics workflows.LEARN MORE
[H2] Support with a heart
Great technology deserves a remarkable customer experience to match. We believe a thoughtful, human-first approach to delivering great support is as important as building great products. Our Customer team genuinely cares about your success and strives to act as an extension of your own team.LEARN MORE
[H2] Trusted security standards
Keeping your data safe and secure in the MotherDuck nest is our top priority. Our robust security and privacy program uses a defense in-depth strategy to protect your most valuable business assets and fortify trust. MotherDuck is SOC 2 Type II and GDPR compliant, with full reports and HIPAA BAAs available on request for Business Plan customers.LEARN MORE
[H2] FAQS
[H3] What is a MotherDuck Organization?
In MotherDuck, an Organization (Org for short) is a team of users. Each Org has member limits aligned to your pricing plan. Accounts for team members and service accounts will count towards the Org members included in your pricing plan.
[H3] How does MotherDuck calculate and meter compute hours?
Depending on the Instance Type, MotherDuck meters compute on demand or per-instance. For detailed information on compute pricing and metering, please refer to our pricing documentation.
[H3] How does MotherDuck define active users?
MotherDuck meters and bills based on the number of unique active human users in your organization per calendar month. Active users are individuals who sign into MotherDuck in a given calendar month.
[H3] What are service accounts?
Service accounts are organization-owned, non-human accounts used by applications, jobs, and infrastructure (such as dbt, schedulers, CI/CD pipelines, or BI tools) - they are metered and billed separately from active users.
[H3] What is MotherDuck’s storage minimum, and how is it calculated and metered?
MotherDuck uses cloud object storage. Usage is metered on the size of compressed data stored on-disk.
To provide data recoverability, MotherDuck charges for 7 days’ worth of fail-safe data stored and meters on a per-day basis. Any data that is mutated or deleted will be retained for 7 days.
MotherDuck does not charge you for: Data managed by you in your own object storage bucket, data stored on your laptop, or MotherDuck-managed data used to provide zero-copy clones called shares and associated data sharing features.
[H3] How are AI Units measured and metered?
1 AI Unit = $1.00
Please refer to the Documentation for a detailed overview of how AI units burn down against SQL Assistant and Bulk AI Functions.
Paid Plan customers have full access to FixIt, MotherDuck’s in-line suggestions to help resolve common SQL errors, and usage-based pricing for SQL Assistant and Bulk AI Functions.
Free Plan users have full access to FixIt and limited access to our SQL Assistant Functions.
[H3] In which cloud regions is MotherDuck available?
MotherDuck is currently available in three AWS regions: us-east-1 (N. Virginia), us-west-2 (Oregon), and eu-central-1 (Frankfurt). If you need a different region, please add your request to Canny.
[H3] Can I use MotherDuck in two cloud regions simultaneously?
Each MotherDuck Organization is currently scoped to a single cloud region that must be chosen at Org creation when signing up.
[H3] Is there an on-premises version of MotherDuck?
No - MotherDuck is a managed cloud service.
[H3] Does MotherDuck have a free trial?
Yes - we offer a free 7-day trial of the Business plan with full access to all features. We also offer a Lite plan with 10 GB of storage and 10 hours of Pulse compute per month included.
[H3] Does MotherDuck have an annual plan?
Yes - teams who are interested in an annual contract have the option to pre-commit to a level of MotherDuck usage. To learn more, please connect with our Sales team.
[H3] How does MotherDuck protect my data?
MotherDuck is committed to protecting customer data, honoring your global privacy rights, and securing the data you provide to us through the use of our products. We build our platform using best practices for highly available, scalable, and secure cloud applications, and we regularly monitor and assess our program to ensure that it meets or exceeds compliance and regulatory requirements. For more information and details about our privacy and security programs, please visit our Trust & Security page.
[H3] Does MotherDuck have academic discounts for schools or students?
We do not currently have any discounts for schools or students. Anyone is welcome to use MotherDuck’s Free Plan.
[H3] Does MotherDuck offer a discount for non-profits?
We do not currently have any discounts for non-profits. Anyone is welcome to use MotherDuck’s Free Plan.
[H3] What is your refund policy?
Please refer to MotherDuck’s Terms of Service for more information. If you have additional questions, please reach out to our Customer team for assistance.
[H3] Try Motherduck now
Get started for free,
share data with the whole flock as you grow.Try 7 Days Free

HYPERTENANCY
[H1] Dedicated compute
Full isolation.
Give each user, customer, or AI agent a dedicated instance — fully isolated, independently sized, and scaled to zero when idle.GET STARTED FREEVIEW DOCUMENTATION
[IMG: Diagram showing an AI agent and human users routing through MotherDuck to individually sized Duckling instances (Mega, Standard, Pulse) that connect to internal and end-user databases]
[H2] Scale Vertically and Horizontally
Manage DuckDB compute instances by user, then add read scaling replicas for read-heavy workloads.UICurlPython
[IMG: Scaling UI]
We were able to identify specific organizations, and even better, specific users, who need more compute. We can scale individually for each one, so we get a much faster UX without paying to scale an entire cluster.Josh NakkaCo-Founder @ Pricemedic
[IMG: Josh Nakka]
Read the Case Study
[H2] A More Flexible Compute Model
[IMG: Table showing example organizations with their service accounts and assigned Duckling configurations such as mega, standard, and pulse read-scaling]
How It Works
[H3] One Duckling per user, scaled independently
Hypertenancy allows you to manage compute instances independently for sub-second query performance with dramatically lower costs. Provision Pulse instances for your agents, speedy Standards for your most important app users, or a Mega for that backfill — you'll only pay for what you use.
[IMG: Illustration of an AI agent sending multiple parallel queries to a Duckling instance showing 70% compute utilization at 3,655 of 5,000 units]
For Agents
[H3] Sandboxed for AI Agents
Agents can generate SQL without running amok. Hypertenancy sandboxes each agent's compute, so a runaway query can't blow up your bill or take down your warehouse.
[IMG: Diagram of three users each connected to their own independently sized Duckling instances, all routing queries to a shared SaaS platform and database]
Read Scaling
[H3] Scale out for read-heavy workloads
Attach read-scaling replicas to individual compute instances to handle read-heavy workloads from agentic applications and business intelligence tools. Scale instances independently with as many replicas as you need.READ SCALING DOCS
[IMG: Cost efficiency chart comparing a flat Legacy Warehouses cost line against MotherDuck]
Cost Efficiency
[H3] Stop paying for idle resources
With other warehouses, you provision for peak and pay for that capacity always. Using hypertenancy, you get a serverless architecture built for real-world workloads.LEARN MORE ABOUT COSTS
[IMG: Flowchart showing the REST API lifecycle: a service account triggers Duckling provisioning, data loading, query serving, and automatic idle spin-down for multiple concurrent users]
Admin API
[H3] Manage programmatically
Create service accounts and provision compute programmatically via our REST API. Each user-internal or end-user-gets a dedicated duckling that spins up on first query and scales to zero when idle. No cluster scaling or tuning required.ADMIN API DOCS
[H2] FAQS
[H3] What is Hypertenancy?
Hypertenancy provisions a dedicated DuckDB instance (Duckling) per user or customer, providing full compute isolation. Unlike traditional multi-tenant warehouses that share a single cluster, each tenant's queries run on isolated compute — heavy workloads from one tenant cannot impact others. Read more in the customer-facing analytics documentation.
[H3] What sizes of Compute Instances are available?
MotherDuck compute instances are called Ducklings. Each Duckling operates as a single-node instance of DuckDB, offering sub-second query performance without the network latency of distributed query engines. Ducklings are independently sized: Pulse, Standard, Jumbo, Mega, Giga. Read more about instance types.
[H3] How do I manage Compute Instances in my application?
MotherDuck provisions ducklings automatically per service account. Create a service account for each customer, generate read/write tokens, and connect using `md:<database>` connection strings. Your app uses tokens to route queries; MotherDuck handles instance lifecycle, scaling, and spin-down.
[H3] What is Read Scaling?
Read scaling allows you to provision read replicas for use in read-heavy workloads, like concurrent use of business intelligence tools. This feature provides high availability and performance, while maintaining your ability to separately provision read/write instances. Learn more about read scaling.
[H2] Bring your architecture to the Duck side
Deploy sandboxed agents, built responsive applications, or simply power up your data stack with sub-second queries for every user.Try MotherDuck FreeREAD THE CFA GUIDE