Onum vs Cribl vs Realm: Security Data Pipelines Compared

TL;DR: If you’re comparing Onum vs Cribl, you should also consider Realm. Onum, Cribl, and Realm all reduce the volume of security telemetry coming into your SIEM, but they’re built with different teams and priorities in mind. Onum is now Falcon Onum, the “real-time security data control plane” that is part of CrowdStrike’s Falcon Next-Gen SIEM. Cribl is an independent data engine covering IT, observability, and security. Realm is the SOC-aware security data pipeline, built for security telemetry and the only one of the three that checks a proposed reduction against the detections you actually run before it ships. Realm’s customer, Vensure, cut FortiGate log volume by 83% and saved $254,901 per year with zero detections lost. Calculate your SIEM savings in ten seconds.

Sending every log and event to the SIEM is expensive, especially considering that much of that data may not even need to be there. For teams looking to get security data volume under control, that can lead to an Onum vs Cribl comparison for shortlisting.

As a security data pipeline vendor ourselves, we’d also like to put Realm into the mix and recommend you consider Realm when you are thinking about Onum vs Cribl (or any other data pipeline solution).

Below, we compare Onum vs Cribl across their key capabilities and differences, alongside Realm. We built Realm, so this comparison naturally comes from a vendor perspective, but that said, we’ve aimed to represent Onum and Cribl fairly, including where each may be the better fit.

What a Security Data Pipeline Does

A security data pipeline (SDP) sits between your log sources and your destinations, cleaning, standardizing, and enriching security data before sending it where it needs to go.

With an SDP, you can keep sending your SIEM the logs it needs for detection and investigation, while routing lower-value data to cheaper storage. That cuts ingest costs significantly and leads to a more efficient SOC.

What Is Realm?

Realm is the SOC-aware security data pipeline that sits between security data sources and destinations like a SIEM or a data lake. Security teams use Realm to reduce, enrich, redact, and transform their data before it reaches those destinations.

Realm analyzes your environment, recommends the right action for your data with the reasoning shown, and proves the impact on your own data. What you cut from your SIEM stays in Realm’s retention layer, Data Haven, as a complete, searchable copy.

In 2026, we won a 2026 Global InfoSec Award at RSA and were also recognized in the Cybersecurity Excellence Awards as Best Cybersecurity Startup.

We also more than doubled our customer base during Q1 2026. Among our new customers is a Fortune 500 materials science company that uses Realm to reduce SIEM costs while maintaining detection coverage.

Onum vs Cribl vs Realm: Which Security Data Pipeline Is the Right One for You?

The right option will depend on what you want your security data pipeline to do, who will manage it, and which security tools you already use.

In general, Realm is a good fit for security teams focused on SIEM cost reduction and detection coverage, Onum is a strong fit for organizations that already use CrowdStrike, and Cribl suits teams needing a broader pipeline spanning security, IT, and observability.

How We Compared Onum vs Cribl vs Realm

All the information below on Onum and Cribl is from their own websites, documentation, blogs, and published case studies, which we reviewed at the time of writing. Everything we say about Realm is from our own product knowledge and what we see in evaluations.

Side by Side Comparison: Onum vs Cribl vs Realm

Before we get into the full breakdown of Onum vs Cribl vs Realm, here’s a quick table with the key differences at a glance.

Company background

Each company was built around a different approach to managing security data.

Onum was founded in 2022 and was acquired by CrowdStrike in 2025, which then integrated Onum as a real-time security data control plane for Falcon Next-Gen SIEM.

Cribl was founded in 2018 by three former Splunk employees. The platform is designed to manage telemetry across security, observability, and IT use cases.

Realm was founded in 2024 and built specifically for security teams. It is the SOC-aware security data pipeline.

Products

All three vendors offer a security data pipeline, but their broader product portfolios are structured differently.

Onum is sold as CrowdStrike Falcon Onum, a real-time data pipeline integrated with the Falcon platform. It parses and enriches logs in motion, applies noise reduction, filtering, masking, and shaping at the source, and routes to SIEMs, data lakes, analytics tools, and storage.

The interface is a drag-and-drop pipeline builder. CrowdStrike notes that Falcon Onum does not need Falcon Next-Gen SIEM and can be deployed independently.

Onum supports inline detections, including Sigma rule evaluation and IOC matching, though only on routes to destinations other than Falcon Next-Gen SIEM. Detections for Next-Gen SIEM run inside the SIEM itself on CrowdStrike Parsing Standard telemetry. Onum can still forward the detection results, meaning tags, flags, and metadata, to other destinations.

Cribl’s products include:

• Stream, the pipeline and flagship offering, which collects telemetry and then routes and filters it before sending it on.
• Edge, an agent for collecting data closer to the source.
• Search, which queries data wherever it is stored without moving it first.
• Lake, object storage for data you route into it, Cribl’s cloud or your own bucket.
• Cribl AI, AI tooling layered onto the pipeline for sensitive data detection, query writing, and observability.
• Cribl.Cloud, the fully managed SaaS version of the platform.

Realm consists of the following:

• Realm Platform, which is a security data pipeline itself. It reduces, enriches, redacts, transforms, and routes security telemetry.
• Realm Clarity AI, the intelligence layer inside the Platform. It profiles your sources, models what each destination needs, builds the filtering rules, and shares them with your team for approval.
• Detection Integrity, which checks every proposed cut against the detections you already run and reports what was reduced and what was protected.
• Data Haven, the searchable retention layer that keeps a complete copy of your history automatically with no configuration needed on your side, and resupplies the exact events an investigation requires.
• Privacy Guard, the governance and redaction layer, which discovers and masks PII, PHI, and PCI in stream before data reaches your SIEM.

Who each platform is built for

Each platform suits different organizations depending on their requirements and technical resources.

Onum is best for CrowdStrike customers and security teams who want a SIEM with a built-in security data pipeline. Though it can be used independently, Onum makes the most sense if you already use Falcon.

Cribl is built for large, mature teams with enough security engineering and observability resources to implement and continually manage a high-touch telemetry pipeline.

Realm is built for organizations that want to optimize the data that’s flowing into their existing SIEM and manage the pipeline themselves without needing a dedicated data engineering team.

How reduction rules get built

The three platforms differ in how data reduction rules are created and how they decide which data can be safely reduced.

Onum gives your team a visual pipeline builder for creating reduction rules. You choose which data you want to target and set the conditions for what should be kept or removed before it reaches the SIEM.

Cribl provides prebuilt Packs as a starting point, but a Pack is written for a source in general (i.e., it is not generated from your environment). Adapting and maintaining them for your own setup is your job. Beyond what ships, you write the rules yourself.

Realm generates rules from your own data. After you connect a source, Realm samples the logs to work out which fields carry the most volume, then checks those fields against a knowledge base of that vendor’s product to establish what each field is actually used for. From there, Realm builds filtering rules and shows them to your team for approval.

Validating what gets filtered out

Reducing data is one thing, proving that you haven’t removed data your detections rely on is another. Onum, Cribl, and Realm take different approaches to this.

Onum lets you test a pipeline before publishing it and inspect what happens to the data at each stage, including what goes into and comes out of each filtering step. Once the pipeline is running, you can compare the volume of data coming in and going out.

Onum’s documentation does not describe automatic validation of reductions against the detections running in your SIEM, so determining whether filtered data is needed for detections is your responsibility.

Cribl reduces data according to the filtering logic you configure. Data Preview, Cribl’s tool for testing a pipeline before you deploy it, shows you what a rule does to your events, including which ones it removes. However, it doesn’t tell you whether removing them affects a detection you run.

Realm validates data reduction rules against the security detections your organization actually uses, including detections written in Sigma, SPL, KQL, CrowdStrike CQL, and other common formats, so it doesn’t accidentally remove data that those detections need. If it can’t safely reduce the data without risking breaking a detection, Realm flags the detection that prevented the reduction instead of making the cut.

Recommendations run first in a staging mode against live telemetry, so you can see the projected reduction and impact, with nothing changing in production until your team approves it.

The output is a report showing you what was reduced, which detections were protected, and your MITRE ATT&CK coverage before and after. You can share this document with leadership, internal audit, or an examiner when asked whether a cut had any impact on monitoring.

You re-run the check when your detections change, and Realm checks and updates the data reduction rules to make sure the data your current detections need is still protected.

Running detections in the pipeline

The three platforms also differ in whether security detection logic can run directly in the data pipeline or remains in the SIEM.

Onum can execute detection logic in motion. It evaluates Sigma rules and matches IOCs as data moves through the pipeline, then forwards the results as tags and metadata. This is supported when sending data to destinations other than Falcon Next-Gen SIEM. Detections for Next-Gen SIEM run inside the SIEM itself on CrowdStrike Parsing Standard telemetry.

Cribl can also run detections in motion. Stream-native detections in Cribl Stream evaluate normalized and enriched telemetry as it moves through the pipeline, aimed at relatively simple, high-confidence conditions such as known-bad indicators, policy violations, canary events, and other “atomic tripwires.” When one is detected, Cribl can alert, route, or fast-track the relevant data.

Realm does not run security detections within the pipeline, and that is by design. Realm reads the detections you already run and uses them to decide what is safe to cut. Your detection logic stays in your SIEM and Realm protects the data it depends on.

Reduction in numbers

All three vendors publish volume or cost reduction figures.

CrowdStrike claims storage cost reductions of up to 50% and 40% less ingestion overhead. However, it footnotes these as projected estimates from its own internal analysis and from metrics recorded during pre-sale evaluations, so they describe modeled benefit, not an actual customer outcome.

Cribl’s case studies note a 48% cut in overall data intake at Sophos, a 41% cut in daily EDR volume at Sally Beauty, and a 40% reduction in SIEM spend at Yale New Haven Health.

Neither CrowdStrike’s nor Cribl’s figures tell you that filtering out security data didn’t weaken or reduce the organization’s ability to detect threats. We think it’s a question that everyone should ask any vendor in this category, including us.

Realm is the only one of the three that can provide a reduction number and proof that detection coverage held.

Realm’s customer Vensure Employer Solutions, a US benefit and payroll provider with more than 10,000 employees, cut FortiGate firewall log volume going into Sumo Logic by 83% and saved $254,901 a year by filtering out routine firewall connection logs, redundant authentications, and benign system events (and keeping denied connections, unusual port activity, and policy violations — the events that cause a firewall detection rule to trigger an alert).

“Realm’s Data Filtering module allows us to remove data that would never be needed for detection or an investigation. This saves us a significant amount of operational budget, which can be repurposed for other strategic priorities. This is a game-changer for budget-constrained security teams.”

Dwayne Smith, Sr. VP Information Security and Global CISO, Vensure Employer Solutions

Further proof of this in action is that Realm’s customer base more than doubled in the first quarter of 2026, including a Fortune 500 materials science company.

Retention and retrieval

You can retain data outside the SIEM with each of the three platforms, but they differ in what gets stored (and how), as well as how you search it.

Onum can send data to external storage such as Amazon S3 for long-term retention. You can later resupply that data through Onum and re-ingest it into the SIEM when needed.

Cribl Lake is a cloud-based object storage for retaining full-fidelity data over the long term in open formats. You can decide what data to store, set retention and access policies, and query it using Cribl Search. Note that it only holds what you actively route to it.

With Realm, you can either bring your own storage or use ours.

If you already have a data lake or object store, Realm can route security data there while parsing, enriching, and tagging it with OCSF observables before it is stored.

If you don’t, you can use Realm Data Haven, a managed, searchable retention layer within the platform. It automatically keeps a complete, immutable raw copy of your security data, including events filtered out before they reach your SIEM, without requiring per-source configuration.

You can search the full history by time range, source, and observable without having to write queries, then resupply only the events you need to whichever destination you use. Data Haven is priced on ingest, meaning search and resupply are unmetered. The format is open and portable, so your history stays usable across any SIEM.

AI-driven optimization

All three vendors use AI to help optimize security data pipelines, but they vary in how much of those optimizations are initiated by the AI itself.

Onum takes a copilot approach. Its AI-powered chat assistants respond to user prompts to build pipeline structures and configure individual processing steps. Its documented AI capabilities therefore focus on helping users make changes to the pipeline rather than proactively optimizing the flow of telemetry on their own.

Cribl also takes a largely copilot-based approach to pipeline optimization. Its Copilot Editor is an AI assistant that builds pipelines from plain-language prompts. It suits individuals learning how the platform works, admins who have taken over an existing deployment and need to move without first learning the configuration syntax, and anyone who wants to test whether AI speeds up the work of turning intent into working logic. The output is a suggestion that you can review, adjust, or take parts of to add into pipelines you build yourself.

Realm takes the most proactive approach to AI of the three. Realm Clarity AI analyzes your telemetry to identify optimization opportunities and recommends rules without waiting for users to prompt it. Those recommendations are then tested against live data and your detections, with changes requiring human approval before they are applied to your live environment.

Keeping the pipeline running

Onum, Cribl, and Realm all provide ways to monitor pipeline health and protect data when something goes wrong. The difference between each of these vendors is in how much setup and ongoing maintenance each requires.

Onum monitors the health of pipelines, sources, and destinations, showing any errors, alerts, and changes in the amount of data flowing through them. If a destination becomes unavailable, persistent queues can buffer data to disk and deliver it once connectivity returns. Administrators can drill into individual errors and logs to diagnose problems.

Cribl can alert you when a source stops sending data or a destination becomes unhealthy, but administrators must configure those notifications and define the conditions that trigger them. Some destinations support persistent queues.

Realm manages the security data pipeline for you. This means that it is by far the easiest of the three when it comes to getting and keeping the pipeline running. Integrations are destination-aware, so parser updates are handled automatically when vendors change log formats. Monitoring learns normal behavior baselines for each integration, without requiring administrators to set thresholds manually. Every destination includes a 14-day persistent queue that automatically resupplies the destination once it’s back online, with no configuration or data limits.

Sensitive data

Each platform can mask sensitive data before it reaches its destination, but how data is identified and how much you have to configure is not the same.

Onum can mask, hash, or redact sensitive fields as data moves through the pipeline. Your team chooses which fields to protect and how, with built-in options for data such as credit card numbers. For automatic detection of sensitive information, Onum can integrate with Google DLP to identify and protect it before the data reaches its destination.

Cribl can mask sensitive data using its Mask function or Cribl Guard. With the Mask function, your team defines the regex that identifies the sensitive data and how matching values should be masked or replaced, and maintains those rules as needed. However, Cribl Guard is only available for Cribl Stream Enterprise plan users and is billed separately on the volume of data scanned.

Realm has Privacy Guard, which classifies data by field-level profiling (not pattern matching), so there is no regex to write or maintain and no requirements to know in advance which fields have sensitive values. It discovers and masks PII, PHI, and PCI in-stream before data reaches your SIEM, data lake, or a third party, with coverage mapped to HIPAA, PCI-DSS, GDPR, and CCPA. Masking preserves schema and structure, meaning that parsing, correlation, and detection logic keep working. Authorized investigators can retrieve unredacted values from Data Haven.

Pricing and total cost

While all three vendors base pricing partly on data volume, the way they calculate usage differs, which can affect the overall cost.

Onum prices based on the volume of data ingested. CrowdStrike customers using Falcon Flex can use their committed spend across the CrowdStrike portfolio.

Cribl uses a credit-based consumption model. You buy credits and use them across Cribl products. Different Cribl products use those credits at different rates. If you have cloud workers running, they use credits even when they’re not processing any data. When considering Cribl costs, it’s also a good idea to take into account engineering time and the cost of professional services to implement Cribl.

Realm is priced on average daily ingestion. Data Haven is also charged based on ingestion volume. Once the data is there, searching or resupplying it to another system doesn’t incur additional usage charges.

Deployment timelines

Onum does not publish a typical end-to-end deployment timeline. All we know from its documentation is that cloud infrastructure is provisioned automatically by Onum, while on-premises deployments are set up with its Customer Success team or partner.

CrowdStrike says Onum’s native integration with the Falcon platform removes onboarding friction, which could make adoption more straightforward for existing Falcon customers.

Cribl sells tiered activation packages delivered by its own consultants, scoped at 90 days or less, with the higher tiers adding access to a consultant for six months afterward, which on the Platinum package works out at four two-hour sessions a month.

Realm is live in 7 to 10 days with no professional services required, making it the most transparent and likely the fastest of the three by far when it comes to deployment.

How to Run a Low-Risk Evaluation of Onum vs Cribl vs Realm

Pick your noisiest log source and run it through whichever of the three security data pipelines you are considering, in parallel with what you have now.

Remember to look not just at the volume a platform cuts, but also whether that reduction affects your detection coverage. With Realm, seven days on one source will give you a reduction figure and a coverage report for your own environment.

Getting Started

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