SIEM vs. SOAR: Key Differences

Your SIEM flagged hundreds of events overnight. Seventeen of them look genuinely suspicious. The rest? Noise from legitimate cloud activity, scheduled maintenance, and that one developer who always tests at 3 AM.

Security teams at cloud-native companies face this tension daily: you need visibility to detect threats, but visibility alone can lead to alert fatigue. That's where SIEM and SOAR come in — two technologies that sound similar but solve fundamentally different problems.

This guide breaks down what SIEM and SOAR do, how they differ, and which your team needs based on your current situation.

What Is SIEM?

Security Information and Event Management (SIEM) is the detection layer of your security operations. It aggregates security data from across your infrastructure into a centralized system for analysis and threat detection.

Security teams use SIEM to gain visibility across systems that otherwise operate in silos. Logs from cloud services, identity providers, endpoints, network devices, and applications flow into a single searchable system. This centralization enables threat detection by connecting events across sources that otherwise operate in silos.

How SIEM Works

The threat detection process starts with log collection. Your SIEM pulls data from cloud services, endpoints, identity providers, and network devices, then normalizes everything into a consistent, searchable format. This normalization step is important because, without it, you'd need to write and maintain separate detection rules for every cloud provider and every log format.

Once data is normalized, correlation engines analyze events in real time, looking for patterns that span multiple sources. When someone fails five login attempts and then succeeds from an unfamiliar location, your SIEM connects those dots across your identity provider logs, VPN logs, and application access logs — something no single system could catch on its own.

These correlation patterns are codified as detection rules, typically mapped to MITRE ATT&CK techniques like credential stuffing (T1110) or privilege escalation. When a rule triggers, the SIEM generates an alert enriched with the context analysts need to act: which user, which asset, what technique was detected, and why it matters.

Types of SIEM Platforms

SIEM platforms come in several deployment models, each with distinct tradeoffs for security teams:

• On-premises SIEM runs entirely within your data center. You own the hardware, manage updates, and control scaling. Best for organizations with strict data residency requirements. Legacy vendors like IBM QRadar are built for this model.

• Cloud-based SIEM is hosted by the vendor as SaaS. They handle availability, updates, and scaling — but your security data lives in their environment. Microsoft Sentinel fits this category.

• Cloud-native SIEM is purpose-built for modern infrastructure: serverless compute, object storage, elastic scaling without capacity planning. Panther takes this further with detection-as-code: analysts can write detections in Python, SQL, or YAML, version them in Git, and deploy through CI/CD like any other software. For teams without coding expertise, Panther also offers a Simple Detection Builder.

• Hybrid SIEM combines on-premises collectors with cloud-based analysis. Best for air-gapped environments or legacy systems that can't send logs directly to cloud endpoints.

Regardless of deployment model, SIEM provides the audit trail regulators require for SOC 2, PCI, and HIPAA compliance. The fundamental value is centralized visibility into what is happening across your entire security environment.

What Is SOAR?

Security Orchestration, Automation, and Response (SOAR) is the action layer of your security operations. It executes the response steps your team would otherwise perform manually after a threat is detected. Think about it this way: SIEM is your nervous system detecting threats, while SOAR is your muscle memory.

SOAR helps SOC teams by eliminating repetition. Your analysts know exactly how to respond to a phishing report: extract the sender, check the URL against threat intel, search for other recipients, quarantine matching emails, and document everything. But doing this 50 times a day burns hours on mechanical steps rather than on actual analysis.

Without SOAR, responding to a single phishing report takes a lot of time: manually copying indicators into threat intel lookups, searching mailboxes one by one, documenting actions in a ticket, notifying affected users. With SOAR, the same response completes much faster — and the analyst only touches it once to make the containment decision.

How SOAR Works

SOAR operates through playbooks — predefined workflows that specify which actions to take when specific conditions occur. These playbooks blend automated data collection, human decision-making, and automated response execution.

A typical phishing response playbook can look like this:

1. The user reports a suspicious email via the phishing button

2. SOAR automatically extracts sender address, URLs, and attachments

3. SOAR queries threat intel feeds for known malicious indicators

4. SOAR searches all mailboxes for emails from the same sender

5. An analyst reviews the evidence and decides if the email is legitimate, spam, or an active threat requiring containment

6. Upon confirmation, SOAR quarantines matching emails across all affected mailboxes

7. The system notifies the reporting user and their manager

Step five is where human judgment matters. The analyst decides whether the "suspicious" invoice PDF is actually a spear-phishing attack targeting finance or just a poorly formatted email from a real vendor. That contextual decision requires business knowledge that automation can't replicate.

This orchestration happens through bidirectional API integrations. SOAR platforms integrate with SIEMs, EDRs, firewalls, identity management systems, and ticketing platforms.

SIEM vs. SOAR: Core Differences

SIEM detects threats by correlating events across your infrastructure, while SOAR automates the responses to those threats by executing predefined playbooks across your security tools.

The fundamental distinction comes down to detection versus action. 

SIEM answers the question "what's happening?" by collecting logs from across your environment and finding patterns that indicate threats. 

SOAR answers "what do we do about it?" by executing the response steps your team has defined. One identifies problems; the other fixes them.

This split means different data lifecycles. SIEM retains everything — you need months or years of historical logs for investigations and compliance. SOAR is transactional: it extracts indicators from an alert, enriches them, executes the playbook, then moves on. SIEM is your archive; SOAR is your assembly line.

The skill sets don't overlap much either. SIEM requires detection engineers who understand log formats, can write correlation rules, and know how attackers move through systems. SOAR requires automation engineers who can map workflows, integrate APIs, and build reliable playbooks. Small teams often start with SIEM because detection engineering skills transfer from general security work, while SOAR demands dedicated automation expertise.

Benefits of SIEM

SIEM's core value is turning scattered data into actionable intelligence.

• Centralized visibility: Aggregate logs from cloud services, endpoints, identity providers, and applications into one searchable system — eliminating the need to query each tool separately during investigations

• Cross-source threat detection: Identify attacks that span multiple systems, like credential stuffing attempts that touch your identity provider, VPN, and application logs simultaneously

• Compliance audit trails: Generate the reports regulators require for SOC 2, PCI, and HIPAA — showing who accessed what, when anomalies occurred, and how you responded

• Historical investigation: Retain months or years of log data to support incident investigations and forensic analysis

• Reduced detection time: Correlation rules and real-time analysis surface threats faster than manual log review

Benefits of SOAR

SOAR's core value is turning defined processes into automated workflows.

• Faster response execution: Automate the mechanical steps of incident response to speed up the process

• Consistent outcomes: Every analyst follows the same playbook, reducing variance and ensuring nothing gets missed during high-pressure incidents

• Analyst time reclaimed: Free your team from repetitive tasks so they can focus on complex threats that require human judgment

• Cross-tool orchestration: Execute containment actions across EDR, firewalls, identity management, and ticketing systems from a single workflow

• Scalable response capacity: Handle higher alert volumes without proportionally increasing headcount

How SIEM and SOAR Work Together

SIEM and SOAR aren't competing technologies — they're complementary systems where SIEM detects threats, and SOAR orchestrates responses. But the traditional integration pattern creates friction that many teams underestimate.

The Traditional Integration Pattern

In a typical SIEM + SOAR deployment, here's what happens when your SIEM detects an impossible travel alert — a user logging in from New York, then London 20 minutes later:

1. SIEM detects the anomaly and generates an alert with basic context: username, timestamps, IP addresses, and geolocation data

2. Alert forwards to SOAR via API, triggering an enrichment playbook

3. SOAR enriches the alert by querying threat intelligence feeds for the IP addresses, pulling the user's role and department from HR systems, and checking asset inventory for the devices involved

4. Analysts receive the enriched alert and begin manual investigation: Is this user known to travel? Do they use a VPN that might cause false positives? What did they access after the suspicious login? Are there other indicators of compromise in the last 24 hours?

5. Analyst makes the call — legitimate activity, false positive, or real threat requiring containment

6. If action is needed, SOAR executes the response: deactivates the account, revokes sessions, creates an incident ticket, and notifies the user's manager

The enrichment helps, but the bottleneck remains: Step four still generally takes 15 to 30 minutes per alert. The analyst needs to manually piece together context, query historical logs, check related events, and build enough confidence to make a decision.

Multiply that by more than 50 alerts per day, and investigation — not response execution — becomes the real-time sink.

Beyond the investigation burden, the separate-systems approach creates operational friction:

• Integration maintenance: API connections break when vendors update their platforms, requiring ongoing engineering attention

• Context fragmentation: Investigation context lives in SIEM, response history lives in SOAR, case management might live in a third system

• Skill set sprawl: Your team needs SIEM expertise for detection engineering AND SOAR expertise for playbook development

• Cost multiplication: You're licensing, maintaining, and training on two enterprise platforms

AI-Powered Investigation Layer

Cloud-native SIEM platforms with AI capabilities eliminate the bottleneck in manual investigation between detection and response.

Panther is an example of this approach: a cloud-native SIEM with detection-as-code capabilities plus Panther AI for automated alert triage and investigation. Panther AI provides AI-powered alert summarization, transparent reasoning with full-context explanations, and can assist with detection writing and tuning.

Here's the same impossible travel scenario with an AI-powered investigation:

1. SIEM detects the anomaly using detection-as-code rules written in Python.

2. Panther AI automatically investigates, enriches with threat intelligence, pulls the user's authentication history, and analyzes behavioral patterns. It also checks for related suspicious activity across other log sources and provides a risk assessment with transparent reasoning that shows the evidence chain.

3. Analysts review the AI's conclusion in seconds — seeing the enrichment data, evidence chain, and the AI's confidence level — rather than spending more than 20 minutes building that picture manually.

4. If action is needed, the analyst can integrate with SOAR platforms (like Torq) to execute automated responses or take manual containment actions.

The key differentiator: Panther AI eliminates manual investigation, the biggest time sink in most SOC workflows. Detection-as-code means security rules live in Git, test in CI/CD, and deploy like any other software — fitting naturally into engineering-driven teams. And Panther's security data lake architecture means no vendor lock-in; your data stays in open formats you control and is queryable with any tool.

Teams using this approach report significant efficiency gains:

• Docker reduced false-positive alerts by 85% and tripled log ingestion by implementing detection-as-code workflows. Investigation times dropped from hours to minutes.

• Cockroach Labs saved $200,000 in OpSec expenses by consolidating its security stack with Panther's detection-as-code platform.

Which Approach Does Your Team Need?

The right architecture depends on where your bottleneck is today. Teams struggling with visibility need SIEM first. Teams drowning in manual investigation benefit most from AI-powered SIEM. Teams with mature detection but repetitive response execution tasks need SOAR. 

Here's how to identify which applies to you.

When You Need SIEM First

You need SIEM when visibility gaps are your primary problem. You're ready for SIEM when:

• You lack centralized logging across cloud services and identity providers — SIEM lets you detect threats like credential stuffing (MITRE ATT&CK T1110) by correlating failed logins across systems.

• Your team spends more time gathering data than analyzing it — SIEM centralizes log queries so you can investigate incidents across multiple sources from one place.

• Compliance requires audit trails you can't currently provide — SIEM generates reports showing privileged access to production systems for SOC 2, PCI, and HIPAA.

• You need to identify patterns that span multiple systems — like detecting data exfiltration through unusual S3 bucket access patterns that no single tool would catch.

Plan for a significant lead time before adding SOAR. The SIEM implementation should precede SOAR investment by 12 to 18 months to establish detection maturity. That includes onboarding critical log sources, writing and tuning detection rules, building documented incident response playbooks, and training your team on investigation workflows.

When You Add SOAR

You need SOAR when repetitive response execution tasks consume significant team capacity. You're ready for SOAR when:

• Your SIEM demonstrates maturity with false positive rates below 20%, so you're not automating noise

• You've documented repeatable incident response playbooks for at least 5 to 10 common scenarios — these become your automation templates.

• Your team handles high alert volumes, with more than 40% of capacity devoted to executing response steps, making triage automation for high-volume, low-complexity events a clear win.

• You need to orchestrate containment actions across multiple tools (EDR, firewall, identity management) rather than manually clicking through each console during incidents.

• You want to standardize response workflows so every analyst follows the same playbook, reducing variance and ensuring consistent outcomes.

SOAR orchestration requires bidirectional API communication with SIEM, EDR, identity management, and network security platforms. Without these integrations, SOAR implementation becomes a significant technical challenge. 

Teams using a cloud-native SIEM like Panther with AI investigation capabilities may find they need less SOAR investment, since AI handles the investigation work that traditionally consumes the most analyst time.

When AI-Powered SIEM Makes Sense

You benefit most from AI-powered SIEM when:

• You're already treating infrastructure as code — detection-as-code fits naturally into your engineering workflow

• Alert investigation is your bottleneck

• You want to avoid vendor lock-in with an open data architecture

• You need to scale the investigation capacity without increasing headcount

Modern SIEM platforms increasingly incorporate AI and automation capabilities, blurring the traditional SIEM-SOAR boundary. 

Common Questions About SIEM and SOAR

Security teams evaluating these platforms often ask the same questions. Here are direct answers to the most common ones.

Does SOAR Replace SIEM?

No. SOAR and SIEM serve complementary roles in security operations. SIEM provides the detection and correlation engine that identifies threats. SOAR provides the automation framework that orchestrates responses. SOAR without mature SIEM means automating against poor-quality alerts — creating more noise than value. e.

Can Small Teams Use SOAR Effectively?

Yes, but timing and scope matter. Teams with 6 to 10 people can implement SOAR successfully, but only when they've matured their detection capabilities, documented repeatable playbooks for at least 5 to 10 common incident scenarios, reduced false-positive rates to below 20%, and demonstrated an alert volume that justifies automation.

The key is to start narrow, focusing on the highest-volume, most repetitive tasks that consume your team's time.

What About AI-Powered SIEM?

Modern SIEM platforms increasingly incorporate AI-augmented workflows that automate investigations that previously required manual analyst effort. Panther AI, for example, provides AI-powered alert triage and summarization with transparent reasoning — showing enrichment data, evidence chains, and risk score, so security teams can verify its assessments rather than relying on black-box decisions.

Cloud-native architectures enable rapid deployment without infrastructure management overhead, consumption-based pricing that scales with usage, and more than 60 native integrations with cloud, SaaS, and endpoint sources, reducing the complexity of custom development.

Choosing the Right Tool for Your SOC

Choosing between SIEM and SOAR comes down to where your team is actually stuck:

• Visibility gaps? You need SIEM to centralize logs and build detection capabilities.

• Investigation overload? You need an AI-powered SIEM that automates the analysis work that’s consuming your analyst’s time.

• Response execution burden? You need SOAR to orchestrate containment actions across tools.

For cloud-native startups and mid-market companies with lean security teams, start with SIEM for visibility and detection. Cloud-native platforms with AI investigation capabilities, such as Panther, can often eliminate the need for separate SOAR investment by automating the most time-consuming part of the workflow. This manual investigation turns a 30-minute task into a 30-second review.

The critical question isn't "SIEM or SOAR?" but rather "what's consuming my team's time today?" Answer that, and the architecture decision follows.

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