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Cybersecurity · head to head

IBM QRadar vs Lambda

IBM QRadar logo

IBM QRadar

Cybersecurity

Enterprise SIEM licensed by events per second, whose cloud business IBM sold to Palo Alto Networks in 2024.

From
On request
Rated
-
Full reviewWebsite
Lambda logo

Lambda

Cloud

GPU supercomputers for AI training and inference at enterprise scale

From
On request
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: IBM QRadar iBM sold the QRadar SaaS business to Palo Alto Networks in 2024 and those customers are being moved to Cortex XSIAM, so anyone buying today is choosing an on-premises product whose vendor has publicly moved the cloud future to a competitor, and the support horizon becomes a contract negotiation rather than an assumption.; Lambda no free tier or trial, requiring immediate commitment for testing
  • They diverge on capability: IBM QRadar covers Offence model, Lambda covers Superclusters.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which IBM QRadar and Lambda actually diverge.

Attributes where IBM QRadar and Lambda differ
AttributeIBM QRadarLambda
Pricing modelsubscriptionPay-as-you-go hourly pricing with volume discounts for reserved capacity
PlatformsWeb, ApiCloud
CategoryCybersecurityCloud
Founded19112012

Identical on both: starting price (On request), free tier (No), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in IBM QRadar

  • Offence model
  • Network flow analysis
  • Device Support Modules
  • Ariel query language
  • Rules and building blocks
  • Deployment topology
  • App Exchange
  • Use Case Manager

Only in Lambda

  • Superclusters
  • 1-Click Clusters
  • On-demand instances
  • Liquid cooling
  • InfiniBand networking
  • Managed orchestration
  • Co-engineering support

What people use each for

The jobs each tool is most often brought in to do.

IBM QRadar

  • A regulated enterprise that must keep log data on premises or in a specific jurisdiction and cannot use a shared SaaS SIEMnot Lambda
  • A SOC that wants log correlation and network flow analysis in one platform rather than buying an NDR product separatelynot Lambda
  • An existing QRadar estate deciding whether to stay on premises or accept the migration path to a different vendor's platformnot Lambda
  • Compliance-driven log retention and reporting where the audit requirement is specific about collection, retention and reportingnot Lambda

Lambda

  • Training foundation models at scale with dedicated GPU infrastructurenot IBM QRadar
  • Large-scale inference serving on enterprise-grade hardwarenot IBM QRadar
  • Multi-GPU distributed training with InfiniBand networkingnot IBM QRadar
  • Single-tenant secure compute for regulated industriesnot IBM QRadar
  • AI lab infrastructure for frontier model developmentnot IBM QRadar

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

IBM QRadar

  • IBM sold the QRadar SaaS business to Palo Alto Networks in 2024 and those customers are being moved to Cortex XSIAM, so anyone buying today is choosing an on-premises product whose vendor has publicly moved the cloud future to a competitor, and the support horizon becomes a contract negotiation rather than an assumption.
  • Licensing is by events per second and flows per minute, so every additional log source raises the cost directly and teams routinely exclude verbose sources such as DNS, proxy, endpoint and cloud audit logs to stay under the licence, which strips out exactly the data an investigation later needs.
  • It needs a dedicated operator: rule tuning, parser work and offence triage are continuous jobs, and an organisation that deploys QRadar without at least one named engineer accumulates thousands of unreviewed offences and a false sense of coverage.
  • A log source without a matching Device Support Module arrives unparsed, and writing a custom parser with regular expressions against an unfamiliar payload format is specialist work that can take days per source, which quietly determines which systems ever get monitored.
  • On-premises capacity is planned across consoles, processors, collectors and data nodes, so outgrowing the sizing means procuring and racking more appliances rather than changing a subscription tier, and growth becomes a purchasing cycle measured in months.

Lambda

  • No free tier or trial, requiring immediate commitment for testing
  • Single-tenant Superclusters require custom pricing discussions
  • Pricing complexity across multiple GPU types and cluster sizes
  • Less suitable for experimentation or small teams with tight budgets

Pricing, plan by plan

IBM QRadar

On request
  • QRadar SIEMFree
    • Event and flow processing
    • Offense management
    • Threat intelligence
  • QRadar CloudFree
    • Cloud-native deployment
    • Elastic scaling
    • Managed infrastructure
  • QRadar SuiteFree
    • SIEM + SOAR + XDR
    • Unified analyst experience
    • Federated search

Lambda

On request
  • 1-Click Clusters B200$undefined/hourly
    • 16 GPUs: $9.86/GPU/hour
    • 256+ GPUs: $8.87/GPU/hour
    • 1-year+ reserved discounts available
  • 1-Click Clusters H100$undefined/hourly
    • 16 GPUs: $6.16/GPU/hour
    • 256+ GPUs: $5.54/GPU/hour
  • On-Demand Instances B200$undefined/hourly
    • SXM6: $6.69/GPU/hour
  • On-Demand Instances H100$undefined/hourly
    • SXM: $3.99/GPU/hour

Which should you pick?

Choose IBM QRadar if

  • You need offence model.
  • You work on Web, Api.
  • You also want network flow analysis.
IBM QRadar review

Choose Lambda if

  • You need superclusters.
  • You work on Cloud.
  • You also want 1-click clusters.
Lambda review

Questions people ask

Is IBM QRadar or Lambda better?
Neither clearly leads. IBM QRadar starts at On request and Lambda at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, IBM QRadar or Lambda?
IBM QRadar starts at On request and Lambda at On request.
Does IBM QRadar or Lambda run on more platforms?
IBM QRadar runs on Web, Api. Lambda runs on Cloud.
What is IBM QRadar best used for?
IBM QRadar is most often used for a regulated enterprise that must keep log data on premises or in a specific jurisdiction and cannot use a shared saas siem, a soc that wants log correlation and network flow analysis in one platform rather than buying an ndr product separately, an existing qradar estate deciding whether to stay on premises or accept the migration path to a different vendor's platform, compliance-driven log retention and reporting where the audit requirement is specific about collection, retention and reporting. Of those, a regulated enterprise that must keep log data on premises or in a specific jurisdiction and cannot use a shared saas siem and a soc that wants log correlation and network flow analysis in one platform rather than buying an ndr product separately are not what Lambda is typically brought in for.
What can IBM QRadar do that Lambda cannot?
IBM QRadar covers Offence model, Network flow analysis, Device Support Modules, Ariel query language. Lambda covers Superclusters, 1-Click Clusters, On-demand instances, Liquid cooling.

Answered from the vendors’ own pages

IBM QRadar: Who owns QRadar now?

It is split. IBM sold the QRadar SaaS assets to Palo Alto Networks in a deal announced in May 2024 and closed that September, and those customers are being migrated to Cortex XSIAM. IBM retains and supports the on-premises product.

Lambda: What makes Lambda's infrastructure different?

Lambda offers single-tenant Superclusters with exclusive GPU access, liquid cooling, and NVIDIA Quantum-2 InfiniBand networking. The company is 100% focused on AI infrastructure with co-engineering support from teams who built infrastructure for major AI labs.

Source
IBM QRadar: Is QRadar being discontinued?

IBM has committed to continuing support for on-premises customers, including security updates, while offering migration assistance. The cloud product's future belongs to Palo Alto. If you are signing a multi-year term, get the support horizon written into the contract.

Lambda: How does pricing work for large clusters?

1-Click Clusters pricing ranges from $5.54-$9.86 per GPU/hour depending on GPU type and cluster size, with volume discounts for 256+ GPUs. Reserved capacity is available at custom pricing for 1-year+ commitments.

Source
IBM QRadar: How is it licensed?

By events per second for logs and flows per minute for network data, with the software or appliance sized to that rate. Add-on modules in the suite are licensed separately.

Lambda: Which GPU types are available?

Lambda offers NVIDIA B200, H100, A100, and Tesla V100 GPUs. Individual instances range from V100 at $0.79/hour to B200 SXM6 at $6.69/hour. Newer models like Vera Rubin are available in Superclusters.

Source
IBM QRadar: What is an offence?

QRadar's term for a correlated case. Rules group related events and flows against a common indicator such as a host or user, so an analyst reviews one offence rather than the hundreds of events behind it.

IBM QRadar: Do I need a full-time engineer?

In practice yes for anything beyond a small deployment. Parser development, rule tuning and offence triage do not stop, and the most common failure mode is a well-installed QRadar that nobody has tuned since go-live.

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