Update advocacy_docs/edb-postgres-ai/analytics/quick_start.mdx

Co-authored-by: Artjoms Iskovs <[email protected]>
EnterpriseDB · Dec 9, 2024 · 9874a20 · 9874a20
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diff --git a/advocacy_docs/edb-postgres-ai/analytics/quick_start.mdx b/advocacy_docs/edb-postgres-ai/analytics/quick_start.mdx
@@ -98,7 +98,7 @@ We expect all introspection queries to work, and if you find one that doesn't, t
 ### Understand the constraints
 
 * Every cluster uses EPAS or PGE. So expect to see boilerplate tables from those flavors in the installation when you connect.
-* Queryable data (like the benchmarking datasets) is stored in object storage as Delta Tables. Every cluster comes pre-loaded to point to a storage bucket with benchmarking data inside (TPC-H, TPC-DS, Clickbench) at scale factors 1 and 10.
+* Queryable data (like the benchmarking datasets) is stored in object storage as Delta Tables. Every cluster comes pre-loaded to point to a storage bucket with benchmarking data inside (TPC-H, TPC-DS, Clickbench) at scale factors from 1 to 1000.
 * Only AWS is supported at the moment. Bring Your Own Account (BYOA) is not supported.
 * You can deploy a cluster in any region that is activated in your EDB Postgres AI Account. Each region has a bucket with a copy of the
 benchmarking data, and so when you launch a cluster, it will use the benchmarking data in the location closest to it.