A SQL-powered framework for instrumenting, monitoring, and analyzing operating systems across Linux, macOS, and Windows.
osquery is an operating system instrumentation framework that exposes OS data as a relational database, allowing users to write SQL queries to monitor and analyze system state. It solves the problem of fragmented, low-level OS telemetry by providing a unified, high-level interface for exploring processes, network connections, hardware events, and more. This enables efficient security monitoring, compliance checks, and operational insights across diverse environments.
Security engineers, DevOps professionals, and system administrators who need to monitor, audit, or analyze operating system behavior across large fleets of servers or endpoints. It is particularly valuable for teams managing heterogeneous environments (Linux, macOS, Windows) and those focused on threat detection, compliance, or forensic investigations.
Developers choose osquery because it replaces custom scripting and disparate tools with a standardized, SQL-based approach to OS instrumentation, reducing complexity and increasing expressiveness. Its unique selling point is treating the operating system as a queryable database, which simplifies real-time monitoring, historical analysis, and integration with existing data pipelines or security platforms.
SQL powered operating system instrumentation, monitoring, and analytics.
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Allows writing expressive SQL queries to inspect system data like processes, network connections, and file hashes, making complex analyses straightforward without custom scripting.
Supports Linux, macOS, and Windows with a unified schema, enabling consistent monitoring and auditing across heterogeneous environments from a single interface.
Offers a simple plugin and extensions API for custom tables, with a comprehensive existing schema covering numerous OS abstractions, as detailed on osquery.io/schema.
Supports ad-hoc exploration via an interactive shell, scheduled monitoring across hosts with osqueryd, and integration into custom applications using Thrift APIs.
Building from source is encouraged but non-trivial, and configuring for large-scale deployments often requires additional, unendorsed fleet management tools, adding overhead.
SQL queries are primarily poll-based rather than event-driven, which may miss fleeting system events or introduce latency compared to kernel-level monitoring solutions.
The project does not endorse or test third-party fleet managers, leading to potential compatibility and support issues for users relying on tools like Fleet or Kolide.