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Imply Lumi Loglake Now Generally Available, Making Security Data in Data Lakes Immediately Searchable
[September 14, 2026]

Imply Lumi Loglake Now Generally Available, Making Security Data in Data Lakes Immediately Searchable


Imply, the company behind Lumi, today announced the general availability of Lumi Loglake, enabling security teams to search unstructured machine data directly in data lakes without predefined schemas, data catalogs, rehydration, or duplicate pipelines.

Security telemetry is outpacing security budgets, forcing organizations to decide what data to keep, how long to retain it, and what to leave behind. At the same time, AI is increasing the value of historical security data because more historical context makes investigations and automated analysis more effective.

Data lakes offer a more economical way to retain that data, but making it usable is still a challenge. Security teams often have to move or prepare data for analysis, or use a separate search environment to access it.

Lumi Loglake makes security data in object storage immediately searchable from the tools teams already use. Organizations can retain large volumes of telemetry in cost-efficient object storage and search it where it lives, including S3, and open in data lake formats such as Apache Iceberg, Delta Lake, Parquet, JSON, and GZIP.

"Security teams shouldn't have to choose betwen keeping the data they need and being able to use it," said Eric Tschetter, Chief Architect at Imply. "That's the problem we built Loglake to solve. Teams can keep more history in object storage and search it when they need it, without changing how their analysts work."

Lumi Loglake provides a unified search and access layer across hot, real-time workloads and historical logs. Security tools and AI applications can access the same underlying telemetry. Analysts can continue using the query languages, dashboards, and detections they already know.

With Lumi Loglake, organizations can:


  • Search logs in-place: query unstructured machine data directly in object storage without schemas, catalogs, or data preparation.
  • Keep existing workflows: Preserve familiar query languages, dashboards, detections, and analyst processes across hot and historical data.
  • Decouple compute and storage: Use always-on compute for real-time monitoring and on-demand compute for historical and investigative workloads.
  • Create one access layer for security data: Give security tools and AI models/agents access to the same underlying telemetry.
  • Put more history to work: Retain more security data cost-effectively, and make it available for investigations and AI agents.

The general availability of Lumi Loglake advances Imply's vision for a more open, AI-ready approach to security data; one that allows organizations to retain more telemetry, make it accessible across tools, and put historical data to work without creating another silo or forcing analysts to change how they work.

Lumi Loglake is generally available today. Visit imply.io to learn more.

About Imply

Imply is the company behind Lumi, a modern data layer built to help organizations search and analyze high-volume machine data. Founded by the original creators of Apache Druid®, Imply helps organizations analyze event-driven data at scale. Imply is backed by a16z, Bessemer Venture Partners, Khosla Ventures, and Thoma Bravo. Learn more at Imply.io.


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