fix

Author: szarnyasg

_posts/2025-05-19-the-lost-decade-of-small-data.md

@@ -130,6 +130,6 @@ From a user perspective, it matters much more that those queries complete in som
 
 What is perhaps more interesting is that back in 2012, it would have been completely feasible to have a single-node SQL engine like DuckDB that could run complex analytical SQL queries against a database of 6 billion rows in manageable time – and we did not even have to [immerse it in dry ice this time](https://youtu.be/H1N2Jr34jwU?si=xCxQqZcLs8WA_5Yl&t=1763).
 
-History is full of “what if”s, what if something like DuckDB had existed in 2012? The main ingredients where there, vectorized query processing had [already been invented in 2005](https://www.cidrdb.org/cidr2005/papers/P19.pdf). Would the now somewhat-silly-looking move to distributed systems for data analysis have ever happened? The dataset size of our benchmark database was awfully close to that 99.9% percentile of input data volume for analytical queries in 2024. And while the retina MacBook Pro was a high-end machine in 2012, by 2014 many other vendors shifted to offering laptops with built-in SSD storage and larger amounts of memory became more widespread.
+History is full of “what if”s, what if something like DuckDB had existed in 2012? The main ingredients were there, vectorized query processing had [already been invented in 2005](https://www.cidrdb.org/cidr2005/papers/P19.pdf). Would the now somewhat-silly-looking move to distributed systems for data analysis have ever happened? The dataset size of our benchmark database was awfully close to that 99.9% percentile of input data volume for analytical queries in 2024. And while the retina MacBook Pro was a high-end machine in 2012, by 2014 many other vendors shifted to offering laptops with built-in SSD storage and larger amounts of memory became more widespread.
 
 So, yes, we really did lose a full decade.