RunLLM

Currently, MotherDuck does not support setting hard spending or budget limits directly on your account. You can monitor your compute and storage usage via the Billing Page in the UI, but this is not updated in real time and may have up to a 1-hour delay. The team is working on adding ways to set budget limits in the future, but this feature is not yet available according to MotherDuck documentation and recent support responses.Would you like more detail on monitoring usage or available cost management features?Sources: - MotherDuck documentation

If you see a "local duckdb not found" error, it usually means the DuckDB extension or binary is missing or not properly installed in your environment. Ensure DuckDB is installed and accessible, and that any required extensions (like the DuckDB Postgres extension) are loaded if your workflow depends on them. For more details on CLI installation and usage, see DuckDB CLI: Installation and Connecting to MotherDuck and DuckDB CLI API.Would you like more detail on troubleshooting or setup steps?Sources: - DuckDB CLI: Installation and Connecting to MotherDuck - DuckDB CLI API

The DuckDB & MotherDuck documentation I have ingested does not mention how to use or integrate MotherDuck with Terraform. If you are looking to automate MotherDuck resource provisioning or management via Terraform, please specify which aspects (e.g., database creation, user management, secrets, etc.) you are interested in, as this context could help clarify your needs. If this doesn't help, please reach out to the DuckDB & MotherDuck support team for further assistance.

Querying a view in DuckDB or MotherDuck does not inherently introduce a performance penalty compared to querying a table, because a view is just a stored SQL query and is not materialized; the underlying query is executed each time the view is referenced. The performance depends entirely on the complexity of the view's SQL and the underlying data sources, not on the fact that it is a view itself. According to the documentation, "the query is run every time the view is referenced in a query" and is not physically materialized, so performance is equivalent to running the underlying query directly on the tables involved in the view (DuckDB CREATE VIEW Statement).However, if the view is defined over complex joins, aggregations, or other expensive operations, or if it is used in a way that prevents query optimizations (such as filter pushdown), you may observe slower performance compared to querying a simple table. The key factor is the SQL logic inside the view, not the view mechanism itself (DuckDB CREATE VIEW Statement).Would you like more detail or examples on how view complexity can affect performance?Sources: - DuckDB CREATE VIEW Statement

Views in MotherDuck are created using standard SQL CREATE VIEW syntax, just like in DuckDB. The view definitions are stored in the metadata and reflect the results of their underlying queries, so querying a view always returns the latest data from its source tables. For example, you can create a view with CREATE VIEW v1 AS SELECT * FROM tbl; and then query v1 as if it were a table. Views are listed in the database catalog and can be queried, but they do not store data themselves—only the SQL definition is stored and executed on demand. According to DuckLake documentation, this is the standard behavior for views in DuckDB and, by extension, in MotherDuck.If you need more detail on how views interact with data sharing, permissions, or hybrid execution in MotherDuck, let me know.Sources: - DuckLake documentation: Views

MotherDuck does not natively integrate with Supabase, but you can connect MotherDuck to Postgres databases (like those managed by Supabase) using DuckDB's Postgres extension—however, this must be done locally, as MotherDuck does not yet support the Postgres extension server-side. You can use DuckDB to read from your Supabase Postgres instance and then write or sync data into MotherDuck for analytics or sharing. See MotherDuck Docs: Loading Data from Postgres for step-by-step instructions.If you want to use Supabase as a data source for MotherDuck, you will need to run DuckDB locally, connect to your Supabase Postgres instance, and then transfer data into MotherDuck. Direct, server-side integration between MotherDuck and Supabase is not currently available or documented. Would you like more detail on the workflow or example code for this process?Sources: - Loading data from Postgres

To set up MotherDuck with Power BI, install the DuckDB ODBC driver and the DuckDB Power Query Connector, then place the .mez connector file in your Power BI Custom Connectors folder. In Power BI Desktop, select "Get Data" → "More...", search for "DuckDB", and choose the connector. For MotherDuck, use md:your_database as the database location and provide your MotherDuck token, which you can obtain from the MotherDuck UI. After connecting, you can select tables, transform data, and build visualizations as usual. For troubleshooting, ensure the Microsoft Visual C++ Redistributable is installed and that your token is valid. DirectQuery and scheduled refresh via Power BI Service are not fully supported yet—refreshes work in Power BI Desktop only at this time.For step-by-step instructions and troubleshooting, see the official MotherDuck Power BI integration guide, and for connector downloads, visit the DuckDB Power Query Connector GitHub. Would you like more detail on any specific step?Sources: - Power BI with DuckDB and MotherDuck | MotherDuck Docs - Troubleshooting Power BI integration

You can create an index in MotherDuck using standard DuckDB SQL syntax, for example: LBKSCREATE INDEX idx_user_id ON users(id);LBKSHowever, while the syntax is supported and the index will be created, indexes in MotherDuck do not currently provide query acceleration—they are only used for enforcing constraints like UNIQUE or PRIMARY KEY, not for speeding up SELECT queries. Queries will still use sequential scans rather than index scans in MotherDuck, even if an index exists. For more, see the MotherDuck CREATE INDEX documentation.Would you like more detail on how indexes behave in MotherDuck or how to use them for constraints?Sources: - MotherDuck CREATE INDEX documentation

It seems likely that table partitioning is not currently supported in MotherDuck, regardless of plan. Multiple sources indicate that native table partitioning (like in Iceberg or Hive) is not available yet, and users are advised to use other strategies if they need partition-like behavior. There is no mention of clustering support either. Indexes are supported, but not partitions or clustering, on any plan including the free tier. If you need partitioning for performance or data management, you may need to implement workarounds such as using multiple tables or manual data organization. Would you like more detail on possible workarounds or future roadmap for these features?Sources: - MotherDuck Community Slack: Partitioning not yet supported

To truncate all tables in DuckDB, you can use the TRUNCATE statement, which removes all rows from a table. However, DuckDB does not support truncating views directly. You would need to drop and recreate views if you want to refresh them. Here's a general approach: 1. Truncate Tables: Use the TRUNCATE statement for each table. 2. Drop and Recreate Views: Use DROP VIEW followed by CREATE VIEW for each view.Would you like more detailed guidance on executing these steps?Sources: - https://motherduckcommunity.slack.com/archives/C058PJL4R0S/p1711382836.342819 - https://duckdb.org/docs/preview/sql/statements/delete