Search longer. Spend less.

Keep notables in your SIEM and move telemetry to data lakes. Ingext stores the dense data where it is cheapest and makes it fast to find when investigations begin.

Why data lakes for security

Most SIEM data is telemetry that is rarely searched in real time. Keeping that bulk in a SIEM makes searches slow and storage expensive. Ingext routes telemetry to data lakes and leaves notables in the SIEM. The result is a smaller, faster SIEM and low-cost storage for the records you still need to investigate.

How Ingext makes search and storage work together

Store dense telemetry in data lakes. Keep notables in the SIEM. Use one search layer to find what matters across long time ranges.

Route telemetry to lakes

Move high-volume records to low-cost data lakes without losing structure or context.

Keep the SIEM small

Retain notables and alerts in a compact index so correlation and triage stay responsive.

Normalize once

Apply consistent fields upstream so security, IT, and data teams work from the same schema.

Search fast at scale

Use Ingext’s search layer to scan long periods across lakes and bring back both hits and helpful field summaries.

Architecture: store where it is cheap, search where it is fast

Collect once, normalize once, and route by purpose. Telemetry goes to data lakes, notables stay in the SIEM, and Ingext provides the search layer that connects them.

Ingext streaming fabric diagram showing upstream routing and data shaping before SIEM ingestion.
Ingext data lakes and search data flow

See search across data lakes

Watch how Ingext routes telemetry to data lakes and keeps notables in the SIEM so investigations stay quick and complete.

Learn how Ingext simplifies data streaming from cloud services to your SIEM platform

Outcomes

Performance

A smaller SIEM responds faster. Telemetry lives in systems built for large scans and long retention.

Cost efficiency

Store dense data in lakes at low cost. Avoid duplicate ingestion and reindexing.

Accessibility

Security, IT, and analytics teams each get the data they need without fighting over one index.

Ease of use

Search across months without moving data. The platform handles routing, health, and backpressure.

Beyond Kubernetes

Kubernetes keeps collectors running, but it does not understand the meaning of the data. Ingext classifies each record and sends it to the right place so search and storage stay aligned with how the data is used.

Routing to Purpose

Traditional architectures treat every record the same. In practice, each dataset serves different consumers with unique performance and retention needs. The streaming fabric routes by purpose — ensuring each system operates at its designed strength.

Security operations

Notables go to the SIEM for correlation and alerting.

IT and network

Metrics and flows go to time-series systems for uptime and performance.

Data science and forensics

Telemetry and history go to Parquet lakes for modeling and deep investigations.

Industry Adoption

The world's leading vendors now treat streaming fabrics as essential infrastructure — improving both performance and clarity.

CrowdStrike + Onum

Upstream routing is now a core layer for performance and clarity.

Cribl

Routing and shaping are recognized as essential building blocks.

Ingext

Adds a fast search layer for data lakes and a processing language for stronger transformation.

All-in-one SIEM storage vs. Data lakes + Ingext search

DimensionTraditional Data PipelineStreaming Fabric (Ingext)
ArchitectureOne big index.Route telemetry to lakes, keep notables in SIEM.
Data HandlingNormalize per tool.Normalize once upstream.
PerformanceSlows as data grows.SIEM stays small, lake scans stay predictable.
Cost ModelPay to ingest everything.Store cheap, search when needed.
AccessibilityExport to share.Direct, secure access per team.
MaintenanceMany brittle feeds.Central orchestration and health.

See normalization in action

See how raw records are normalized once and stored in lakes so they remain cheap to keep and fast to query.

Learn how raw CloudWatch logs are exploded and reassembled into single, usable records for your SIEM

Search longer with a smaller SIEM

Move telemetry to data lakes and keep notables in your SIEM. Ingext connects storage and search so investigations are fast and budgets stay in control.