Comparisons

How the 10x Engine compares to Elastic ILM, and to Elastic's Logsdb index mode + searchable snapshots.

How does this compare to Elastic ILM (Index Lifecycle Management)

ILM moves data to cheaper tiers after you've already paid to index every byte. The 10x Engine cuts what gets indexed: fewer nodes, less compute, less hot-tier SSD from day one.

On self-hosted Elasticsearch or OpenSearch, lossless compaction reduces volume before indexing. On managed Elasticsearch, compact is a no-op, so the real levers there are tier_down, offload, and sample/drop.

	Elastic ILM	10x Engine
When	After ingestion	Before ingestion
What	Move data to cheaper tiers	Reduce volume before indexing (modeled 50%+ on self-hosted)
Ingestion cost	Full volume indexed	Only optimized volume indexed
Hot tier	Full volume on SSD	Modeled 50%+ less SSD on self-hosted

How does the 10x Engine compare to Elastic's Logsdb index mode and searchable snapshots

Both kick in after ingestion. You still pay full compute and node costs to index every byte. Neither reduces your node count.

The before-indexing reduction comes from lossless compaction, which applies on self-hosted Elasticsearch or OpenSearch. On managed Elasticsearch, compact is a no-op, so the levers there are tier_down, offload, and sample/drop.

	Logsdb	Searchable Snapshots	10x Engine
When	After indexing	After indexing	Before indexing
Reduces	Disk footprint (columnar encoding)	Lifecycle storage (S3 frozen tier)	Ingestion compute + storage + nodes
Ingestion cost	Unchanged	Unchanged	Modeled 50%+ less on self-hosted
Node count	Unchanged	Unchanged	Fewer nodes needed