> The fact is, ‘Big Data’ is dead; the simplicity and the ease of making sense of your data is a lot more important than size.
... after which they go saying
> Cloud data vendors are focused on performance of 100TB queries, which is not only irrelevant for the vast majority of users, but also distracts from the ability to deliver a great user experience.
... and then
> Distributed architectures were once necessary to process many analytics workloads. That’s why several of us built Google BigQuery - distributing queries to hundreds or thousands of machines was the only way to achieve adequate performance. This is no longer true.
Given that they lay their foundations around DuckDB, essentially a SQLite pandan but for analytical workloads, it remains to be seen what type of service and workloads MotherDuck aim to target with the platform (DuckDB) which I think is deliberately purposed for non-cloud computing type of things.
> The fact is, ‘Big Data’ is dead; the simplicity and the ease of making sense of your data is a lot more important than size.
... after which they go saying
> Cloud data vendors are focused on performance of 100TB queries, which is not only irrelevant for the vast majority of users, but also distracts from the ability to deliver a great user experience.
... and then
> Distributed architectures were once necessary to process many analytics workloads. That’s why several of us built Google BigQuery - distributing queries to hundreds or thousands of machines was the only way to achieve adequate performance. This is no longer true.
Given that they lay their foundations around DuckDB, essentially a SQLite pandan but for analytical workloads, it remains to be seen what type of service and workloads MotherDuck aim to target with the platform (DuckDB) which I think is deliberately purposed for non-cloud computing type of things.