Hi everyone,
I recently went through the Capella vs MongoDB Atlas analytics benchmark and found it very informative. I’m planning to run some similar tests myself, so I’d like to better understand a few aspects of the methodology to interpret the results correctly.
In particular, I’m curious about:
• The choice of Atlas SQL for the MongoDB analytics side. Since MongoDB also supports analytics through native aggregation and column-store indexes, I’d like to understand the reasoning behind using Atlas SQL specifically.
• The difference in analytics cluster setups (multiple nodes for Capella vs a single analytics node on Atlas) and how that should be interpreted when looking at parallelism and execution times.
• Any general guidance or best practices for running CH2++ or similar JSON analytics workloads, especially when comparing different document databases.
My intention is simply to understand the benchmark more deeply so I can design meaningful tests on my side. Any clarifications or pointers would be greatly appreciated.
Thanks!
PS: sorry, cant provide the benchmark as attachment, i provide it through a swisstransfert link SwissTransfer - Send large files securely and free of charge
