SIEM is often the single largest line item in a security budget, and it grows for a reason security teams cannot control: threats hide in data, so you have to collect more of it. Every new log source, every added data feed, every extended retention window pushes the bill up. This post is about SIEM cost reduction that does not mean collecting fewer security logs, because dropping the data is how you miss the attack.
Why SIEM costs climb
Most SIEM pricing scales with the volume of security data you ingest and retain, whether that is measured in events per second, gigabytes per day, or a compute-based equivalent. Security data is high-volume and only grows: cloud audit logs, endpoint telemetry, network flows, identity events, and application logs all feed the pipeline. Because detection quality depends on coverage, the incentive is to collect everything, which collides head-on with a bill that scales with everything you collect.
The tempting shortcut, filtering sources or shortening retention, is dangerous in security specifically. Attackers operate in the low-frequency long tail, and investigations often reach back weeks or months. As we cover in sampling vs. lossless, the data you drop to save money is disproportionately the data an incident needs.
Reduce SIEM cost by lowering cost per byte, not coverage
The way out is the same one that works for observability: decouple the volume of security data from the cost of keeping it. Sasquatch Labs reduces SIEM cost with lossless compression, shrinking security logs by an order of magnitude or more (security data compresses especially well) while keeping every event. You lower cost per byte instead of lowering coverage, so detection quality and investigation depth are preserved.
The security layer, Yeti, runs detections and correlation directly on that compressed, in-cloud data. Investigations use the Snowman engine and the Signal agentic AI layer, which query the data in place and speak SPL, KQL, LogQL, and more. Nothing is exported to a third party to run analytics, which is both a cost and a compliance win.
Where the savings come from
- Compression. An order-of-magnitude smaller footprint for the same security logs.
- No egress. Running in your own cloud removes the transfer fees of shipping security data to a SaaS platform. See egress costs.
- Affordable retention. Long, mandated security retention stops being a budget problem. See log retention costs.
- Query in place. No separate re-ingestion bill to search or investigate.
The right SIEM cost-reduction strategy makes it cheaper to keep every security log, not cheaper to keep fewer of them.
If your SIEM bill is forcing hard choices about which security logs to keep, the lever to pull is cost per byte, not coverage. See how it works at sasquatchlabs.io, and read about the Splunk alternative for regulated industries.