Sumo Logic vs. Datadog: The Definitive Comparison for 2025

Datadog and Sumo Logic, both offer powerful tools to monitor applications. While they often appear in the same conversations, they were built with different core philosophies that shape their features, costs, and the day-to-day experience for engineers.

Datadog is widely recognized as a market leader in infrastructure and application performance monitoring (APM). Sumo Logic, conversely, established its roots in log management and security analytics, positioning itself as a converged platform for both observability and security operations.

This article provides a definitive, deep-dive comparison of Sumo Logic vs. Datadog. We'll go beyond marketing features to explore the technical details that matter most during implementation and incident response, from data path control to agent overhead.

Core Focus and Philosophy

Understanding the origins of each platform is key to grasping their current strengths.

Datadog's focus is on unified, real-time performance monitoring. It began by providing deep visibility into infrastructure metrics and has since expanded into a comprehensive, all-in-one observability platform. It's designed for DevOps and SRE teams who need to quickly diagnose performance issues across a complex stack, from frontend user experience down to the underlying network.

Sumo Logic’s focus is on converged security and log analytics. It's designed to ingest and analyze massive volumes of log data. This foundation makes it exceptionally strong for deep troubleshooting, compliance, and security investigations. Its key differentiator is the native integration of a Security Information and Event Management (SIEM) solution, creating a single source of truth for development, security, and operations teams.

Feature Comparison

While both platforms cover the three pillars of observability: logs, metrics, and traces. Their feature sets and depth vary significantly.

✓✓ - Feature is fully available ✓ - Partial or limited feature ✗ - Feature is not available

Sumo provides native RUM; synthetic tests are typically surfaced via provider integrations rather than a deep first-party suite.

Under the Hood: Sumo Logic vs Datadog

Beyond feature lists, experienced engineers need to know how these platforms behave under load, how data flows before it hits your bill, and what the operational experience is like during a real incident.

Data Pipeline Control and Cost Management

Controlling telemetry before you pay for it is critical for managing costs at scale. Let's explore how both platforms handle different aspects of data pipeline control and cost management.

Trace Sampling:

Datadog defaults to head-based sampling in its tracers, meaning the decision to keep or drop a trace is made at the beginning of a request. You can achieve more intelligent tail-based sampling (making the decision at the end, once the full trace context is available) by running the OpenTelemetry Collector in front of Datadog.

Sumo Logic ships an OpenTelemetry-based collector that allows for rule-driven filtering and shaping of traces before they leave your environment, giving you direct control over data volume and cost.

Log Ingestion and Filtering:

Datadog processes logs through a series of sequential pipelines before indexing. In these pipelines, you define rules to parse, enrich, or filter your logs. For example, you can create a rule to drop logs with a certain status code to control costs. This pre-processing is powerful but requires you to define the structure of your data upfront.

Sumo Logic, on the other hand, uses Field Extraction Rules (FERs). This allows you to apply parsing logic either as logs are ingested or, more flexibly, at the time you run a query. This "schema-on-read" approach is ideal for unstructured data because you don't need to know how you want to search a log at the time it's collected. However, it means that investigations often rely more heavily on crafting complex queries.

Cold Storage and Rehydration:

Both platforms allow you to archive logs to your own S3 bucket to save costs, but their retrieval mechanics differ.

Datadog’s Log Rehydration reads archived objects from your bucket for the selected time window, then applies your query. Because the query is evaluated after the archive files for that time range are downloaded, scan size and cloud data-transfer costs depend primarily on the time window you choose, not just the query selectivity. Narrowing the time window is the best way to reduce scan size and retrieval cost.

Also, rehydration only supports specific S3 storage classes—Standard, Standard-IA, One Zone-IA, Glacier Instant Retrieval, and Intelligent-Tiering (only if the asynchronous archive tiers are disabled) as documented in Datadog's archive configuration guide.

The implication is that if your S3 lifecycle policies automatically move logs to these colder, cheaper storage tiers to save money, you won't be able to rehydrate them in Datadog without first manually restoring them to a supported class. This adds extra steps and time during an incident or audit when you need urgent access to old logs.

Sumo Logic allows on-demand ingestion from your S3 archive with a 5-minute granularity, pulling data back into the platform when needed.

The term "on-demand ingestion" means you can selectively re-ingest data from a specific time range when you need it. The "5-minute granularity" refers to the precision with which you can specify this time range. For example, you can tell Sumo Logic to pull all logs from 10:05 PM to 10:10 PM on a specific date, allowing you to narrow your focus and control costs by only re-ingesting the exact data you need for an investigation.

Agent Performance and Overhead

The resource footprint of the collector agent is a key planning consideration, especially on busy hosts.

Datadog Agent: The APM path is CPU-bound and scales with spans per second. When CPU is constrained, the Agent buffers unprocessed payloads in memory, which can increase memory usage and risk drops. For sizing, Datadog publishes guidance by throughput—for example, ~70 MB at ~58k spans/s and ~130 MB at ~130k spans/s (Agent 7.39 benchmarks according to Datadog's agent resource guide).

Sumo Logic Collector: This is a Java process with a default heap of 128 MB; planning for 256–512 MB is common depending on sources and volume. It’s designed to handle up to ~15,000 events/sec per collector before you scale out.

Which collector is this?
Installed Collector is Sumo’s Java-based collector (the one with a default 128 MB heap, with guidance to plan 256–512 MB depending on sources and volume). Sumo Logic Distribution for OpenTelemetry is a separate OTel-based collector with different packaging and management; choose it if you want OTel semantics and remote management at scale.

The "Life During an Incident" Experience

How you query and investigate during an outage is a crucial differentiator.

In Datadog, an investigation is often a structured, UI-driven workflow. You might start with a dashboard showing a spike in errors, click on a failing service to view its traces, and then pivot to the logs associated with those specific traces. Because data is parsed and tagged upfront in pipelines, filtering is fast and intuitive. This guided experience is excellent for quickly narrowing down known issues.

An investigation in Sumo Logic is typically query-driven and more exploratory. You might start by writing a broad query to search for error messages across all logs from the last 15 minutes. From there, you would iteratively refine the query, adding keywords, parsing fields on the fly, and grouping results to hunt for anomalies. This approach is incredibly powerful for investigating novel or unexpected issues where the data structure isn't known in advance, which is common in security incidents.

Security, Compliance, and Data Residency

Security Stack Depth

Datadog offers a broad security stack, including Cloud SIEM, Application Security Monitoring (ASM), CSPM, vulnerability scanning, and a first-party SOAR capability integrated with Cloud SIEM and Workflow Automation.

Sumo Logic provides a deeply integrated Cloud SIEM with rich SecOps features and a native Cloud SOAR for automation.

Data Residency

Datadog operates multiple sites (US/EU/APAC including Japan/AP1). Always verify product availability per site during evaluation using Datadog's published site availability guidance.

Sumo Logic pins your account to a chosen AWS deployment region, and data stays within that region. Note that the India (Mumbai) region was deprecated on April 30, 2025, with access fully terminating April 30, 2026—confirm current region availability during procurement.

User Experience and Learning Curve

The day-to-day experience of using each platform is quite different.

Datadog is widely praised for its polished, intuitive, and user-friendly UI. It offers many out-of-the-box dashboards and a guided workflow that makes it easy for new users to get started.

Sumo Logic's UI is powerful but complex, with a steeper learning curve. Its interface is built around a query-centric model. Training: both vendors provide free self-paced learning. Sumo also offers free public instructor-led virtual classes, while both vendors charge exam fees for certifications.

Pricing Models and Total Cost of Ownership

Datadog uses a modular, per-product model with several billing dimensions. At a minimum, you’ll size hosts for Infrastructure and/or APM, then layer on usage-based items like logs, RUM sessions, and custom metrics.

Core Datadog SKUs & Units — list pricing as of Oct 2025

• Infrastructure Pro: $15 per host/month.
• APM: $31 per APM host/month, which also includes a monthly bundle of 1M indexed spans and 150 GB ingested spans per APM host.
• Logs: Two levers—ingest and indexing. Ingest is $0.10/GB; indexing is priced per 1M events and scales with retention (e.g., 7 days $1.27, 15 days $1.70, 30 days $2.50 per 1M events). Flex Logs adds a cheaper storage tier with separate query compute.
• Custom metrics: Billed per 100 custom metrics.
• RUM/Product Analytics: Billed per 1,000 sessions. For example, RUM – Measure is $0.15 per 1K sessions according to Datadog's list pricing.

For a deeper dive into datadog pricing, check out our article on Datadog Pricing Main Caveats Explained.

Sumo Logic primarily uses Flex Licensing, which decouples log ingest from analytics. This means $0 ingest and unlimited users, you pay for storage and scan volume, tracked via credits. This favors a “log everything, pay when you analyze” approach.

How Sumo Logic Flex Works

• $0 Ingest for Logs: For non-SIEM logs, credits are consumed by stored volume and scans. Scans happen whenever queries, dashboards, or monitors traverse data. Sumo provides “scans per GB ingested” profiles (e.g., 500–750, 750–1500, 1500–2000) to help you budget based on analytics intensity. This favors a “log everything, pay when you analyze” approach.
• Metrics: These are measured in Data Points Per Minute (DPM) for billing and reporting, separate from log scans.

What Actually Drives Your Bill

In Datadog, your bill is primarily driven by the number of infrastructure and APM hosts. It's important to monitor auto-scaling and ephemeral nodes, as APM host counting can be based on a high-watermark model.

Beyond hosts, APM costs are affected by the volume of indexed and ingested spans that exceed the included bundle. You can control this by tuning sampling at the tracer or with an OpenTelemetry Collector.

Logs are often the biggest variable. Costs can be managed by trimming data at ingest with agent filters, selectively indexing only high-value streams with appropriate retention, and using Flex Logs for less frequently accessed data.

Finally, costs for products like RUM and Synthetics are event and session-based, so it's wise to forecast traffic peaks. For custom metrics, costs can be controlled by reducing cardinality and using aggregations.

With Sumo Logic, the main driver of your bill is scan intensity. The more you query, especially with wide time ranges or numerous dashboards, the more scan credits you will consume. This can be managed by right-sizing time ranges and using targeted filters.

Storage and retention are also key factors. You choose the retention period for each data source, and older data kept in "hot" storage costs more than data in cheaper tiers or S3.

Activating security features like Cloud SIEM or Cloud SOAR will be a separate entitlement with its own credit rules.

Lastly, for metrics, high-frequency ingestion increases your Data Points Per Minute (DPM). Downsampling where possible is recommended to control these costs.

Conclusion: Which Platform Is Right for You?

The choice ultimately depends on your primary pain points and team structure.

Choose Datadog if your main priority is best-in-class APM and infrastructure monitoring with a rich set of out-of-the-box dashboards and a user-friendly UI. It allows teams to become productive quickly, but be prepared to actively manage costs.

Choose Sumo Logic if your work is log-centric, with a strong focus on security operations and compliance. Its native SIEM and SOAR capabilities, flexible query-driven investigations, and strong compliance posture (especially PCI DSS) make it ideal for SecOps and regulated environments.

Logs, Metrics, Traces in One Place: Meet SigNoz

If you are weighing Sumo Logic and Datadog, add SigNoz Cloud to your shortlist. You keep your OpenTelemetry setup, get one place to investigate issues, and avoid agent lock-in. For a side-by-side view, see the SigNoz vs Datadog comparison.

Why teams evaluating Sumo and Datadog choose SigNoz Cloud

• One UI for incident work
  Correlate a slow trace with related logs and service metrics in a click. No context switching, faster root cause.
• OpenTelemetry first
  Keep the same OTel Collector you already run. Point it to SigNoz Cloud and ship OTLP without re-instrumenting.
• Starts hosted, stays flexible
  Begin on Cloud for speed. If policy changes, move to BYOC or self-host without changing your instrumentation.
• Clear, predictable pricing: Starts at $49/month; then pay for what you use ($0.30/GB for logs and traces, $0.10 per million metric samples). Unlimited teammates. See pricing.

Get Started with SigNoz

You can choose between various deployment options in SigNoz. The easiest way to get started with SigNoz is SigNoz cloud. We offer a 30-day free trial account with access to all features.

Those who have data privacy concerns and can't send their data outside their infrastructure can sign up for either enterprise self-hosted or BYOC offering.

Those who have the expertise to manage SigNoz themselves or just want to start with a free self-hosted option can use our community edition.

Switching from Datadog? Follow the Datadog → SigNoz migration guide to map agents, pipelines, and dashboards.