LibreSpeed VS Onam Security

Onam Security's answer:

One security graph, not a suite. Most "unified" platforms are acquisitions stitched behind a single login — separate data models, separate consoles, findings that never meet. Onam was built from one inventory and one rule model, so connecting a single cloud account activates every capability at once: posture, attack paths, identity, data, containers, SaaS and detection. That design produces things a stitched suite structurally cannot. SaaS posture sits on the same graph as cloud posture, so a Google Workspace admin without MFA and an over-permissive IAM role can be scored as hops on one attack path. And coverage goes deep where others go wide — 11,346 posture rules across 549 services on seven clouds, including OCI, Alibaba Cloud and IBM Cloud, which most competitors treat as a checkbox.

Onam Security's answer:

Three reasons. First, consolidation that is real: one agentless connection replaces six tools and five dashboards, and there is nothing to install — read-only credentials, no sidecars, no daemons on your nodes. Second, prioritisation you can act on. Attack-path analysis cuts thousands of findings to the handful an attacker could actually chain, each mapped to MITRE ATT&CK with hops-to-breach and blast radius, and risk is expressed in dollars via the FAIR model rather than another severity label. Third, breadth without shallowness: 78 compliance frameworks from a single control set, 7 clouds and 8 SaaS platforms on one graph, and rules defined in versioned YAML rather than hardcoded — so coverage is auditable and extensible instead of a marketing number.

Onam Security's answer:

Small and mid-sized security teams carrying enterprise-sized cloud estates. The typical user is a cloud security engineer, security architect or head of security at an organisation running two or more clouds plus a heavy SaaS footprint, responsible for thousands of assets with a team of two to twenty people. They are the teams for whom the six-product approach never worked — not because they could not buy the tools, but because nobody had the headcount to wire them together and triage five queues. Compliance leads are a strong secondary audience, particularly at organisations under multiple overlapping regimes that need one control set to answer to all of them.

Onam Security's answer:

Onam was built by people who have run incident response, threat hunts and cloud architecture reviews — not by a marketing team that later hired security. The frustration that started it was specific: paying for six products, wiring five dashboards, and still missing the finding that mattered. The conclusion was that fragmentation is not a UI problem to be solved with another dashboard; it is a data-model problem. Findings cannot be correlated if each product holds its own inventory in its own schema. So Onam started at the other end — one inventory, one rule model, one graph — and built the capabilities on top of that rather than bolting them together afterwards.

Onam Security's answer:

Python and FastAPI power the backend, with a single backend-for-frontend gateway exposing roughly 166 endpoints across 60 routers, plus Pydantic for validation and SQLAlchemy over PostgreSQL for the inventory and findings data model. Attack-path analysis runs on a Neo4j property graph, per tenant, with roughly 25 catalog-driven edge derivers. All 11,346 posture rules are defined in human-readable YAML and versioned in a catalog — the platform loads and evaluates rules, never hardcodes them. Cloud collection uses provider SDKs and read-only APIs: the AWS SDK, Azure Management API, GCP Cloud Asset API and equivalents. The console is TypeScript, React and Next.js with Tailwind CSS. The platform runs as multi-tenant SaaS.