Topic starter
02/09/2026 1:29 pm
TL;DR: Storing every log in a SIEM can force teams into costly, disruptive replacement projects, while Anomali argues that a normalized data lake under the SIEM can move high-volume telemetry out of ingest-priced storage, preserve detection logic, and keep data searchable. The practical shift is architectural: lower SIEM cost without a forklift migration.
Editorial analysis by NHI Mgmt Group, based on content published by Anomali: “The Security Data Lake Replaces the SIEM's Storage (Without Ripping Out Your SIEM)”.
By the numbers:
- A 100 GB/day Splunk deployment lists around $76,000 a year for the base platform before Enterprise Security is added.
- OCSF joined the Linux Foundation in November 2024.
Key questions
Q: What breaks when a SIEM is forced to store every log source?
A: Cost and operational complexity rise together.
Q: Why does a normalized data lake reduce SIEM risk?
A: It lets teams separate storage economics from detection operations.
Q: What signs show a SOC has outgrown its SIEM storage model?
A: The warning signs are rising ingest spend, repeated pressure to prune logs, long implementation cycles for new sources, and correlation content that is expensive to maintain across multiple telemetry types.
Practitioner guidance
- Define telemetry tiering by detection value Classify sources such as DNS, flow, firewall, and endpoint data by how often they drive active detections versus how much they cost to ingest.
- Move one source at a time Use a source-by-source migration sequence so you can validate alert parity before you retire any SIEM ingest path.
- Normalize events to a shared schema Adopt a common event model so fields remain consistent across cloud, network, and endpoint telemetry when data lands in the lake.
Bottom line: A security data lake under the SIEM changes the storage and operating model without forcing a disruptive replacement project.
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This topic was modified 2 days ago by NHI Mgmt Group
02/09/2026 1:30 pm
Security data lake layering is becoming a governance response to SIEM economic sprawl. The article describes a problem many SOCs already feel: storage pressure forces teams to keep paying SIEM rates for telemetry that is rarely used in primary detections. That is not just a tooling issue, it is a control-design issue because the platform economics now shape what gets retained and what gets analysed. Practitioners should treat telemetry placement as a governance decision, not a storage preference.
A question worth separating out:
Q: How should security teams evaluate security data lakes alongside SIEM investments?
A: Teams should evaluate them by control outcomes, not by storage cost alone. A security data lake is useful when it improves normalization, preserves investigative fidelity, and enables earlier detection logic without locking analytics into one vendor’s schema. If those outcomes are absent, the architecture may only shift costs rather than improve security operations.
👉 Read our full editorial: Security data lakes can reduce SIEM storage without cutover risk
This post was modified 2 days ago by NHI Mgmt Group