We’ve been sold a comforting lie for the last decade.
If you haven't spent a weekend ingesting a billion log lines into ADX and running a summarize across them in under two seconds, you haven't yet understood what "scalable" actually means.
Spark shuffles are the enemy of scalability. ADX uses a concept called extents (immutable compressed column segments). When you scale out, ADX doesn't reshuffle the world. It redistributes the metadata about those extents. The data stays put; the query logic moves to the data. This is why a single ADX cluster can handle 200 MB/s of sustained ingestion and still serve interactive queries.
Your future petabyte-scale self will thank you.
We’ve been sold a comforting lie for the last decade.
If you haven't spent a weekend ingesting a billion log lines into ADX and running a summarize across them in under two seconds, you haven't yet understood what "scalable" actually means.
Spark shuffles are the enemy of scalability. ADX uses a concept called extents (immutable compressed column segments). When you scale out, ADX doesn't reshuffle the world. It redistributes the metadata about those extents. The data stays put; the query logic moves to the data. This is why a single ADX cluster can handle 200 MB/s of sustained ingestion and still serve interactive queries.
Your future petabyte-scale self will thank you.
