Comparison

Security lakehouse vs SIEM.

A SIEM indexes your logs in a proprietary store and charges you by volume. A security lakehouse keeps them as open Parquet you own and runs detection on top. Here is what that difference means for cost, retention, detection and your exit options.

See EDG3 See SIEMonster V5
Side by side

Where they differ.

DimensionSecurity lakehouse (EDG3)Traditional SIEM
Storage formatOpen Parquet on object storage in your tenantProprietary index owned by the vendor
PricingBy endpoint tier, retention includedBy GB/day, EPS or workload
Retention6 months to 7+ years, same price30 to 90 days hot; archive extra
What you collectEverything; volume does not change the billWhat the budget allows; the rest is dropped
Where detection runsAt the endpoint and in the cloudIn the cloud or on central indexers only
When the link dropsDetection and ransomware isolation continue locallyBlind until connectivity returns
Detection logicDetection-as-Code: forkable, diffable, auditable in gitVendor rule packs and a proprietary query language
TriageAI analyst with cited evidence, ATT&CK context, confidence scoreManual, or an add-on SOAR product
Querying your historyAny Parquet engine: Spark, DuckDB, Athena, TrinoThe vendor's search only
LeavingYour data is already in an open formatExport project, often with volume limits
In practice

Three things change on day one.

You stop filtering. The first thing teams do on a lakehouse is turn the firehose back on: full firewall logs, network flow, DNS, endpoint process telemetry. On a per-gigabyte SIEM those are the first feeds cut, and they are also where most intrusions are visible first.

Your retention becomes a security decision rather than a finance one. Investigating a breach that began eight months ago is routine when eight months of data is sitting in Parquet, and impossible when the SIEM kept 60 days.

Your detections stop depending on the cloud. With EDG3 the agent keeps detecting and will isolate a host showing ransomware behaviour whether or not the control channel is up, which is the one moment a cloud SIEM cannot help you.

If you need a conventional SIEM at serious scale today, SIEMonster V5 gives you the open-component, no-EPS-penalty version of that, and you can see how it compares to the incumbent on the SIEMonster vs Splunk page.

FAQs

Lakehouse vs SIEM, answered.

Cheaper is the visible part. The structural difference is that the lakehouse stores data in an open format you own on storage you control, so detection, retention and the exit path are no longer tied to a vendor's index. A SIEM owns the format; a lakehouse does not.
Yes, and many teams start that way: route everything to the lakehouse for retention and investigation, keep the SIEM for the detections and dashboards you already trust, and move rules across over time. With SIEMonster you can also run V5 and EDG3 side by side.
Mature SIEMs have large libraries of vendor content and a proprietary query language your analysts know. A lakehouse uses Detection-as-Code in git and SQL or engine-native queries. The trade is a learning curve against the end of per-gigabyte pricing and lock-in.
Both. SIEMonster V5 is a full cloud SIEM on open components, priced per server. EDG3 is the edge-resident security lakehouse with AI, priced per endpoint tier. The right one depends on whether you need a conventional cloud SIEM at scale or detection and containment that survive a cut link with data that never leaves your estate.

Ready to stop paying by the gigabyte?

Start with EDG3 on edg3.io, or talk to the SIEMonster team about which platform fits your estate.

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