Good analysis and I agree. Another way of phrasing this to consider the power of focus. The engineers working on DuckDB can dedicate all their time and creativity to making their product great. They can keep their teams lean, probably have simple communication structures, and become a super desirable place to work. You can attract the best of the best. I think the component team, feature team conversation comes into play. DuckDB is essentially a component with the limited scope and economy of scale that comes with that. By themselves, they aren't a whole solution. But when combined with other components teams, its a killer product
I struggle with DuckDBs claim to be a "Data Warehouse", it's a single process query engine. It must be combinated and integrated tightly with storage etc to call it a "Data Warehouse." Maybe MotherDuck could be called a Data Warehouse solution if they tightly couple the storage to their compute? Help me understand this. It seems like *most * DuckDB users in the wild are using it place of Pandas for example. No one, *yet*, is replacing Snowflake or Databricks completely with DuckDB yet.
What about Snowflake and Databricks on an Iceberg data lake? Are they then query engines and not lakehouses/warehouses... perhaps so. However, I think this is where things are going.
I think a bigger deal is the in-process part, which Motherduck solves but so does the new Postgres extension as then DuckDB becomes server-based.
there are folks trying to. Take Definite for example. Fully managed BI stack, with duckdb under the covers. Also, people like Jake Thomas has replaced MILLIONS of dollars of Snowflake spend with hundreds of thousands of duckdb spend
Good analysis and I agree. Another way of phrasing this to consider the power of focus. The engineers working on DuckDB can dedicate all their time and creativity to making their product great. They can keep their teams lean, probably have simple communication structures, and become a super desirable place to work. You can attract the best of the best. I think the component team, feature team conversation comes into play. DuckDB is essentially a component with the limited scope and economy of scale that comes with that. By themselves, they aren't a whole solution. But when combined with other components teams, its a killer product
I struggle with DuckDBs claim to be a "Data Warehouse", it's a single process query engine. It must be combinated and integrated tightly with storage etc to call it a "Data Warehouse." Maybe MotherDuck could be called a Data Warehouse solution if they tightly couple the storage to their compute? Help me understand this. It seems like *most * DuckDB users in the wild are using it place of Pandas for example. No one, *yet*, is replacing Snowflake or Databricks completely with DuckDB yet.
What about Snowflake and Databricks on an Iceberg data lake? Are they then query engines and not lakehouses/warehouses... perhaps so. However, I think this is where things are going.
I think a bigger deal is the in-process part, which Motherduck solves but so does the new Postgres extension as then DuckDB becomes server-based.
there are folks trying to. Take Definite for example. Fully managed BI stack, with duckdb under the covers. Also, people like Jake Thomas has replaced MILLIONS of dollars of Snowflake spend with hundreds of thousands of duckdb spend