RunReveal vs. Panther: A Modern SIEM Comparison for Security Teams

If you're evaluating SIEMs and Panther is on your shortlist, this guide is for you. Both RunReveal and Panther market themselves as modern, cloud-native alternatives to legacy SIEMs like Splunk. Both reject the ingest-based pricing model that punishes teams for growing. Both appeal to security engineers who want to treat detection like code.

So what's actually different? Quite a bit, it turns out. Especially when it comes to data pipelines, AI capabilities, pricing transparency, and total cost of ownership. This breakdown covers everything you need to know to make an informed decision.

RunReveal vs. Panther: At a glance

Pricing comparison

RunReveal prices on the data you store (not ingest), with no separate infrastructure bill and no surprise at renewal. AI capabilities, including the Autonomous SOC Agent, are part of the platform, not a tier you unlock later. One number, clearly understood, that doesn't change shape twelve months in.

According to Vendr, “Panther pricing is primarily driven by data ingestion volume measured in terabytes (TB) per month, with additional costs tied to data retention, user seats, and optional professional services.”

RunReveal, comparatively prices on the data you store (not ingest), with no separate infrastructure bill, user seats costs, and no surprise at renewal. AI capabilities, including the Autonomous SOC Agent, are part of the platform, not a tier you unlock later.

Beyond data ingest and storage volumes, the second variable worth understanding is pricing around AI. Panther's AI capabilities, including AI Triage, are not included in all base contracts. For some customers, these features sit behind premium pricing or require renegotiating. That matters if you're choosing Panther today partly for its AI story, since the price you're quoted at signing may not reflect the full cost of the platform you're expecting to use.

The pipeline problem: Native vs. bolted-on

This is where the comparison gets interesting, and where teams evaluating both platforms should spend serious time.

Security environments generate enormous amounts of noisy, low-value log data. VPC flow logs, GCP audit logs, verbose endpoint telemetry: these sources can produce billions of events a day, most of which have no security relevance whatsoever. The ability to filter, enrich, and route that data before it's stored isn't just a nice feature; it's the difference between a manageable security program and one where you're spending a disproportionate chunk of your budget storing noise.

RunReveal ships with Pipelines as a native, first-class platform capability. You can define rules to enrich incoming events with threat intel and asset context, normalize data across sources, filter low-value events before they're stored, and drop irrelevant data entirely, all without leaving the platform, and without paying extra.

Panther historically required external tooling to filter or transform data before it lands in Snowflake: tools like Cribl, Observo, or custom Lambda functions that your team has to build, own, and maintain. In late 2025, Panther acquired Datable, a security data pipeline company, which signals they recognize this as a gap. But an acquisition and a native feature are different things; pipeline capabilities that come via acquisition take time to integrate deeply, and teams evaluating Panther today should ask specifically how those capabilities work in practice and what's included in their contract. What Panther offers is detection-as-code capabilities and post-ingestion normalization.

The practical implication: Panther teams who want robust data preprocessing need to bring their own pipeline layer, which adds engineering overhead, operational complexity, and often additional cost.

What this looks like in practice: Sentry

When Sentry migrated to RunReveal, the savings from native pipelines were almost immediate. Shortly after onboarding, the RunReveal team noticed that Sentry was ingesting a massive volume of unnecessary GCP logs, a configuration issue Sentry wasn't even aware of.

"[The RunReveal team] highlighted a particular log type being ingested. Immediately I wanted to know why we are generating and delivering so many logs downstream?" recalled Geoff Goldsmith, Senior Security Engineer at Sentry.

Within a week, Geoff had traced the issue, fixed the upstream configuration, and eliminated 97% of the wasteful logging. The result: thousands of dollars per year, recovered almost immediately after migration, and with zero additional tooling required.

That outcome isn't possible without a native pipeline layer that gives you visibility into what's flowing through your system and the ability to act on it. RunReveal flagged the issue. The pipelines made it trivial to fix. And because RunReveal's pricing model doesn't benefit from higher data volumes, the team had every incentive to help Sentry spend less.

Detection engineering: Python vs. SQL

Panther's detection-as-code approach has been rooted in using Python, which is genuinely powerful for teams that live in code. The tradeoff is the Python prerequisite. Teams without a strong software engineering background may find the barrier to entry steep. (Panther has recently introduced detections with SQL, which we love to see as we’re a bit biased to SQL-based detections!)

RunReveal uses SQL-compatible syntax for detections, which the vast majority of security analysts and data-savvy engineers already know. For teams moving fast with limited headcount, which describes most high-growth security organizations, that accessibility translates directly into faster detection coverage.

RunReveal also ships with native support for Sigma streaming detections. This means that community-maintained Sigma rules work out of the box, without translation or conversion. Panther supports Sigma rules, but they need to be converted to Python first, an extra step that adds friction when you're trying to respond quickly to a newly published detection.

For teams evaluating both platforms: think carefully about your team's composition and where your time goes. If you have dedicated detection engineers who love Python and want maximum flexibility, Panther's model serves that well. If you want broad analyst accessibility and faster time to coverage, RunReveal's SQL-native approach wins.

AI capabilities: Built-in vs. gated

Panther's AI Triage feature is well-regarded by their users. It provides alert context, reduces false positives, and surfaces investigation suggestions automatically. But there are two things worth understanding before you make a purchasing decision based on Panther's AI capabilities.

First, AI Triage is not universally included in base Panther contracts. For some customers, it's a paid add-on or requires upgrading to a higher tier. If you're evaluating Panther partly because of what you've seen in their AI demos, it's worth getting explicit confirmation of exactly which AI features are included in your contract and at what price, now and at renewal.

Second, Panther's AI is locked to a single underlying model, with no option to bring your own API keys or swap providers. That means you're not just buying Panther's SIEM capabilities; you're also buying into their AI pricing, which can change independently of your SIEM contract. Some teams facing this constraint have chosen to build their own triage workflows outside the platform entirely rather than absorb escalating in-platform AI costs.

RunReveal was built with AI as a first-class architectural concern, and it's included. The Autonomous Security Operations Agent doesn't just add context to alerts. It automates the investigation workflow end to end. When an alert fires, RunReveal’s agent automatically opens a case, runs the investigation, queries across relevant data sources, and updates the case with findings, analysis, and full query history. Investigation work that used to take hours gets done in minutes, with a complete audit trail.

RunReveal also supports BYO-LLM, meaning you can connect your own model provider and API keys rather than being locked to a vendor's AI pricing. For teams that already have enterprise agreements with AI providers, or who simply want cost transparency and control over their AI layer, this matters.

Query language & ease of use

Panther introduced PantherFlow, their purpose-built security query language, to simplify investigation workflows across the Snowflake data lake. The intent is good, making it easier to run complex queries without deep SQL expertise. But it's still a proprietary query language that your team has to learn, and it introduces a dependency on Panther for any complex querying.

RunReveal uses SQL. That's it. Not a SQL-like language with custom extensions. Not a query builder with limited expressiveness. Standard SQL, which your security analysts, data engineers, and developers almost certainly already know. The friction of learning a new query syntax is zero.

Infrastructure & deployment

One of the more overlooked things about RunReveal is that the deployment model adapts to your environment, not the other way around. There are three paths:

RunReveal Cloud is the fastest way to get started. It's a fully managed SaaS with both multi-tenant and single-tenant options, so you get peace of mind on data isolation without taking on any operational overhead. No infrastructure to provision, no ClickHouse cluster to babysit.

BYO-Cloud is for teams that want single-tenant isolation in their own cloud environment but don't want to run and maintain the infrastructure themselves. RunReveal handles the operational layer; you get the data residency control. It's the middle path between fully managed and fully self-hosted.

RunReveal Kubernetes is the fully on-premises option, built for AWS-native or Kubernetes-native environments where data never leaves your infrastructure. This is the right fit for highly regulated industries, FedRAMP workloads, or organizations with security and compliance requirements that rule out cloud-hosted data.

Most teams land on RunReveal Cloud. But the fact that the path to fully on-premises exists, with the same platform capabilities, is meaningful for teams whose procurement process involves data residency questions.

Support & partnership

RunReveal has built a reputation for responsive support. Our customers consistently mention it in reviews. For a growing SIEM company, that customer closeness is a real differentiator compared to the enterprise support queues of legacy vendors.

The Sentry story above is illustrative. RunReveal proactively flagged a cost issue that Sentry didn't know they had. That kind of transparency and alignment is unusual in enterprise software.

"The amount of transparency with RunReveal is the highest I've had with any vendor," said Geoff Goldsmith at Sentry. That's not a line about ticket response times. It's about a fundamentally different kind of vendor relationship.

Who should choose RunReveal

RunReveal is purpose-built for security teams at fast-growing companies that need modern, AI-native SIEM capabilities without the operational overhead or structural misalignment of legacy platforms.

It's particularly well-suited for teams that:

• Want data pipelines without buying a second product or building custom ETL infrastructure
• Need SQL-native querying that's accessible to the whole team, not just Python engineers
• Are scaling rapidly and can't afford a pricing model that surprises them at renewal
• Want AI that doesn't just help with triage, and don't want to pay extra to unlock it
• Want the option to bring their own LLM keys rather than being locked to a vendor's AI pricing
• Value a vendor partner who is more of a partner, and less of a vendor

Frequently asked questions

Is RunReveal a direct Panther replacement? Yes. RunReveal covers the full SIEM use case: log ingestion, normalization, detection, pipelines, alerting, AI investigation. It can replace Panther for any team currently evaluating or using it. RunReveal also offers hands-on migration support.

How does pricing compare? Panther's pricing separates licensing from infrastructure, meaning you'll pay Panther fees on top of your Snowflake and AWS costs, with no cap on how those infrastructure costs scale. Some customers have also found that AI capabilities like Triage are gated behind premium pricing and not included in base contracts. RunReveal's storage-based pricing is all-in: one number that covers the platform, AI included, with no separate infrastructure bill and no surprise at renewal.

What about Snowflake integration? RunReveal is built on ClickHouse, a columnar database optimized for high-performance analytical queries on security data at scale. Teams who prefer Snowflake as their data backend should evaluate Panther's Cloud Connected model. Teams who want a fully managed, fast, purpose-built platform without Snowflake overhead will prefer RunReveal.

Do I need a dedicated pipeline tool with RunReveal? No. RunReveal ships with native pipelines that let you filter, enrich, normalize, and drop data before it's stored. There's no need for Cribl, custom Lambda functions, or other ETL tooling.

How long does it take to get up and running? Most teams are live with RunReveal in days, not weeks. RunReveal's onboarding is designed to get you ingesting data and running detections quickly, and the team works closely with customers through the process.

What query language does RunReveal use? Standard SQL. If your team knows SQL, they can run investigations in RunReveal from day one. No new query language required.

Can I bring my own LLM or AI keys with RunReveal? Yes. RunReveal supports BYO-LLM, so you can connect your own model provider and API keys. This gives you control over your AI costs and lets you take advantage of any existing enterprise agreements you have with model providers. Panther's AI is locked to a single underlying model with no option to bring your own keys.

What does migration from Panther to RunReveal look like? RunReveal provides hands-on migration support and works closely with customers through the transition. Most teams are up and ingesting data within days. If migration anxiety is holding you back from evaluating alternatives, it's worth knowing that RunReveal's team is set up to make that transition as low-friction as possible, including helping translate detection logic and onboard existing data sources.

Getting started

The best way to understand whether RunReveal is the right fit is to see it with your actual data.

Book a demo with the RunReveal team and they'll walk you through the platform tailored to your environment and use cases, and can answer specific questions about migration from Panther or any other platform.

If you're actively evaluating Panther alongside RunReveal, bring your real data questions. The differences in pipelines, pricing, and AI capabilities are most apparent when you're working through your actual detection and investigation workflows.