Most SIEMs were built for large security teams with dedicated administrators and deep implementation budgets. Graylog was built to deliver the same quality of detection without the overhead. Keep reading to learn:
Most SIEMs put you in a position of rationing visibility. Collect what the budget allows, or collect what you actually need to stay protected. With Graylog, that’s not the trade-off. Full coverage. Predictable cost. From day one.
“Predictable cost control allows us to deliver strong security outcomes without limiting visibility. That stability matters for both regulators and customers.”
– Hon Fun Ping, Managing Director, NetAssist
SIEM deployments stall. Architecture decisions, configuration headaches, resource gaps. Suddenly months have passed with no one running an actual investigation. Graylog’s onboarding is structured, well-documented, and built to get your team productive fast.
“[Graylog] has consistently proven to be stable, scalable and reliable for centralized log management and security monitoring.”
– Manager of IT Services, Healthcare Industry
“The tool is very powerful and highly configurable, and the Graylog teams are top-notch, not to mention the well-designed online courses.”
– Manager of IT Services, Healthcare Industry
The difference: If your SIEM needs a separate tool to be affordable, the platform is missing a feature and you’re managing two products instead of one.
Graylog Security includes Data Pipeline Management. The same capability that leads Splunk customers to bolt on a separate tool like Cribl to keep ingest costs manageable. With Graylog, that’s one less vendor, one less product, and one less support contract.
The more important difference is what happens when something goes wrong. Secondary log data that didn’t seem worth the cost of full SIEM ingestion has a way of becoming critical evidence after a breach. With Graylog, that data is in the integrated data lake and it doesn’t count against your license. When an investigation starts, you can search across it directly, confirm it contains what you need, and selectively retrieve only the relevant slice. You’re not paying to process a large dataset to answer a narrow question. You’re not hunting across two systems hoping to find the answer you need.
SIEMs that rely on third-party pipeline tools to control ingest cost, including Splunk, Elastic, Sumo Logic, IBM QRadar, LogRhythm/Exabeam, and Datadog, create an architecture where you’re running two products to solve what should be one problem. Two vendor relationships, two support contracts, two sets of tuning and maintenance, and two failure points when something goes wrong at 2 a.m.
The difference: Where your security data lives should be your decision, not your vendor’s revenue strategy.
Graylog Security runs self-managed on-prem, in your private cloud, in your AWS account, or in Graylog Cloud. Same code base. Same features. You move when it makes sense for you, not when a renewal forces you. The same Graylog runs in 180 countries, including regulated industries, government environments, and global telecom networks where SaaS isn’t an option.
SaaS-only SIEMs including Microsoft Sentinel, Sumo Logic, Datadog Cloud SIEM, Google Security Operations, CrowdStrike Falcon Next-Gen SIEM, and Exabeam New-Scale keep your security data in their environment, on their terms. Microsoft Sentinel is actively consolidating into the Microsoft Defender portal, deepening its dependency on the Microsoft ecosystem. For some organizations, that consolidation is a feature. For governments, regulated industries, and organizations with data residency requirements, it’s often a non-starter.
Self-managed-but-pressuring-cloud SIEMs including Splunk, IBM QRadar, Elastic, and Exabeam-LogRhythm still ship a self-managed product, but the roadmap investment and sales motion all point toward the vendor-hosted version. Splunk customers asking how to move back to on-prem from Splunk Cloud hear the Splunk Community say there is no official path. IBM QRadar customers face a different version of that same message. Palo Alto Networks acquired QRadar SaaS from IBM and announced End-of-Sale and End-of-Life for the product line, with migration to Cortex XSIAM as the stated path forward. On-prem QRadar customers remain with IBM, but new strategic investment has moved elsewhere.
The difference: A risk score is only useful if it tells you where to look next, not which alert is loudest.
Graylog Security scores entities: users, hosts, IPs, not individual alerts. The model is deterministic at the foundation: event severity x asset priority x vulnerability state, amplified by detection chains when activity matches known attack patterns. Then AI does what AI is actually good for, reasoning over the structured risk picture, not guessing at the foundation. Score range 0-100. Transparent. Tunable.
Event-aggregation risk-based alerting, such as Splunk’s Risk-Based Alerting, scores activity into a risk index. Useful, but it scores events rather than entities, and vulnerability state isn’t a native amplifier in the model. Splunk’s own partner community has documented that this approach runs into scaling constraints at high risk-event volumes, requiring architectural workarounds.
UEBA-native platforms including Exabeam, Securonix, and Gurucul lean heavily on entity scoring via machine learning, with a lighter deterministic foundation. Reviewers on Gartner Peer Insights consistently flag false-positive volume, ongoing tuning load, and the AI compute costs that scale with it, as the price of that approach.
The difference: Making a query easier to write is not the same as removing the need to write one. And neither solves the real problem: knowing with certainty what you retrieved.
Graylog Security uses parameterized searches and dashboards to eliminate the query step for analysts who shouldn’t need to write one. A Tier 1 analyst types a username and gets a complete, consistent, scoped view of that entity: logins, locations, anomalies, related alerts, asset risk score. Senior analysts define the underlying logic and retain full query power. That logic executes exactly the same way every time. No LLM interpretation. No prompt variation. No ambiguity about scope. Graylog also includes a native MCP server at every tier. Bring your own LLM to the reasoning layer: investigation summaries, threat context, anomaly explanation. That’s the right job for an LLM. Interpreting what you retrieved. Not deciding what to retrieve.
Proprietary-query-language including Splunk (SPL), Microsoft Sentinel (KQL), and Elastic (ES|QL) built their own DSLs, then launched AI assistants to abstract them because the original syntax was too hard to learn. The natural language promise is real: an analyst who couldn’t write SPL can now describe what they want. But AI-generated queries still generate queries. You don’t know with certainty whether the AI scoped the question correctly, whether a differently phrased prompt would have caught more, or whether the same prompt produces the same results tomorrow. In a live investigation, that uncertainty has a name: incomplete evidence. Evidence that’s incomplete is evidence that’s wrong. Graylog didn’t build a query language that requires an AI to abstract it.
The difference: AI capabilities in your SIEM should be a given, not a negotiation.
Graylog Security includes a native MCP (Model Context Protocol) server at every tier. RBAC is enforced: an AI agent only sees what the assigned user role can see. Bring your own LLM, cloud or on-prem. Use it for natural-language queries, investigation summaries, dashboard explanations, and threat-intel context. No premium add-on. No separate license. No per-prompt billing.
AI as an add-on or a forced upgrade is the reality for several major platforms. Some vendors sell AI capabilities as a separately licensed product entirely: Microsoft Security Copilot carries its own capacity model and pricing structure, and Splunk AI Assistant requires a separate EULA and subscription tier to access. Others lock AI behind their highest pricing tiers: Google SecOps reserves generative AI assistance for Enterprise and above, with agentic AI requiring yet another purchase on top of that; Sumo Logic bundles advanced AI capabilities into its upper-tier plans rather than making them available across the board. Whether you’re facing a separate invoice or a forced upgrade, the result is the same. AI becomes a negotiation, not a given.
The difference: Your detection logic, dashboards, and data should travel with you — not stay behind when a vendor relationship ends.
Graylog Security is fully accessible through our API, a native MCP server, an open-source heritage, and broad outbound integration. Route enriched events to ITSM, case management, BI dashboards, and downstream data lakes. Your detection logic is portable. Your dashboards export. Your investments travel with you.
Closed-ecosystem SIEMs have well-documented export constraints. Sumo Logic’s own documentation lists Recent Searches, Favorites, Scheduled Views, Partitions, Field Extraction Rules, and lookups as not supported for export, with imports capped at 1,000 objects at a time. If your renewal goes sideways, your investment in detection content shouldn’t go with it.
“The simplicity of implementing critical tasks with almost no friction set the standard.The experience stayed consistently smooth and reliable, and I recommend Graylog whenever the topic of SIEM comes up.”
Clear ROI :
Detection speed is non-negotiable for our customers. With Graylog, we can search across massive datasets instantly without restricting logging due to cost.
MTTD improved by 40% (4 hours to under 45 minutes).
Absorbed 300% log volume with no SOC staffing increase.
50% reduction in SIEM licensing costs.
Yes. Run Graylog on-prem, in your private cloud, in an air-gapped environments, in the Cloud provider of your choice, or let us run it for you in Graylog Cloud. Same product, same features.
Splunk is the schema-on-read pioneer, powerful but priced by ingest, which is why Cribl exists as a complementary product. Elastic is schema-on-write like Graylog and has strong search, but no native Data Pipeline Management and ES|QL has a learning curve. Graylog combines schema-on-write, native DPM, an integrated Data Lake, MCP server with RBAC at every tier, and deployment portability.
Yes. Native MCP server. RBAC-enforced, an AI agent only sees what the user role it represents can see. Included at every Graylog Security tier. Bring your own LLM. No premium AI add-on.
Graylog Enterprise and Security includes DPM and a Data Lake in the platform. CrowdStrike Falcon Next-Gen SIEM, Microsoft Sentinel, and Gurucul also offer DPM/data lake capabilities. Most other SIEMs, including Splunk, Elastic, Sumo Logic, IBM QRadar, Datadog, LogRhythm/Exabeam, and Rapid7 InsightIDR, require a third-party tool (typically Cribl) to manage ingest cost and routing.
For mid-enterprise teams, Graylog Open (free, source-available) and Graylog Security (commercial, predictable per-volume pricing) skip the ingest-volume tax that drive Splunk customers to bolt on Cribl. Decide what data you need for advanced detections and place data in a data lake for future investigations for added context.
Palo Alto Networks acquired QRadar SaaS from IBM and announced End-of-Sale and End-of-Life for the product line. On-prem QRadar is still supported by IBM, but new strategic investment has moved to Cortex XSIAM.
Yes. Asset risk scoring, audit-ready reporting, long-term retention via the Data Lake, and Illuminate content packs are built for compliance teams. The self-managed deployment option matters especially for state/local government, education, telecom, and FedRAMP-adjacent workloads where SaaS-only SIEMs face procurement friction.
Yes. Graylog is recognized in the 2025 Gartner Magic Quadrant for SIEM.
Graylog Security is licensed by daily ingest volume, offered in two models. On the fixed-rate model, you commit to a daily ingest tier and pay a flat annual amount regardless of actual consumption — no overage charges if your ingest fluctuates day to day. On the consumption model, you purchase a volume allotment and draw from it throughout the year, which offers more flexibility but may require a mid-year top-up if ingest runs ahead of schedule.
Both models include AI, DPM, Data Lake, and MCP at every tier. Secondary data in the Data Lake does not count against your ingest license. No per-user surcharges. No per-feature unlock fees.
For comparison: Splunk is also ingest-based, but the similarities end at the base model. Splunk’s standard contract terms allow overage billing at list price for exceeding committed volume. SOAR is licensed per user seat on top of the platform. AI capabilities require a separate agreement. And Splunk’s published renewal policy applies a 9% annual price increase. With Graylog, the license you sign is the product you get.
Yes. The same product runs at every scale, from a 5-person IT shop centralizing logs to a multi-region SOC with cluster-to-cluster forwarding. Pricing is volume-based, not headcount-based, so you don’t get punished for growing.
