Top 10 Datadog Alternatives in 2025: What to Choose

Datadog is a comprehensive cloud monitoring and observability platform that provides metrics, logs, traces, and APM (Application Performance Monitoring) in a unified SaaS solution. It's known for its extensive integrations, powerful dashboards, and real-time monitoring capabilities.

However, several factors drive teams to seek alternatives:

1. Cost concerns: Datadog's pricing can scale rapidly with data volume and host count
2. Data sovereignty: Some organizations need on-premises or regional data storage
3. Vendor lock-in: Teams want flexibility and control over their observability stack
4. Complexity: Some teams need simpler solutions for their specific use cases
5. Open source preference: Organizations wanting transparency and customization

In this guide, we'll explore ten alternatives that address these concerns, from open source platforms to specialized SaaS solutions.

Why Teams Are Seeking Datadog Alternatives

• Cost Optimization: Datadog's per-host, per-metric pricing model can become expensive as infrastructure scales. Teams with large Kubernetes clusters or high-cardinality metrics often face unpredictable bills.
• Data Control & Compliance: Organizations in regulated industries or those with strict data residency requirements need solutions that keep data on-premises or in specific geographic regions.
• Flexibility & Customization: Open source and self-hosted solutions offer greater control over data pipelines, retention policies, and customization of dashboards and alerts.
• Avoiding Vendor Lock-In: Using vendor-neutral formats like OpenTelemetry and open standards helps teams maintain flexibility in their observability strategy.

What to Look for in a Datadog Alternative

When evaluating alternatives, consider these key criteria:

Feature	Why It Matters
Unified Observability	Metrics, logs, and traces in one platform reduce tool sprawl and context switching
Cost Structure	Transparent, predictable pricing based on usage or infrastructure size
Data Ownership	Self-hosted or flexible deployment options for compliance and control
Scalability	Can handle growing data volumes without performance degradation
Ease of Migration	Support for OpenTelemetry and standard formats makes migration smoother
Alerting & Visualization	Rich dashboards, customizable alerts, and anomaly detection capabilities
Integration Ecosystem	Support for common tools, cloud providers, and data sources
Community & Support	Active development, documentation, and professional support options

Top 10 Datadog Alternatives: Comparison & Use Cases

Jump to comparison table for Datadog alternatives comparison and use cases.

1. OpenObserve

OpenObserve is an open source Datadog alternative for teams that want unified observability across logs, metrics, and traces without Datadog’s high costs, proprietary lock-in, or usage-based pricing surprises.

OpenObserve Pros:

• Unified Datadog Replacement: Logs, metrics, and traces in one platform, similar to Datadog’s single-pane experience
• OpenTelemetry-Native: Drop-in replacement for Datadog agents using vendor-neutral instrumentation
• SQL Instead of Proprietary Queries: Avoid Datadog-specific query languages and reduce vendor lock-in
• Massive Cost Reduction: 140x compression drastically lowers storage and ingestion costs vs Datadog
• High-Volume Friendly: Handles large Kubernetes and microservices workloads efficiently
• Flexible Alerting: SQL-based alerts comparable to Datadog monitors, without per-alert pricing
• Self-Hosted or Cloud: Full control over data residency and retention
• Predictable Costs: No per-host or per-metric billing model

OpenObserve Cons:

• Smaller integration marketplace compared to Datadog
• Requires SQL familiarity for advanced analysis
• Some enterprise-grade features still evolving

Integration / Mitigation:

• Works with OpenTelemetry Collector as a Datadog agent replacement
• Compatible with Prometheus remote write and existing exporters
• Can run alongside Datadog for phased migrations
• Prebuilt dashboards ease transition from Datadog views

2. Grafana Stack (Grafana + Prometheus + Loki + Tempo)

Grafana Stack is a popular open source Datadog alternative composed of multiple best-in-class tools for metrics, logs, and traces, offering flexibility at the cost of higher operational complexity.

Grafana Stack Pros:

• Strong Datadog Replacement for Metrics: Prometheus is widely considered the industry standard for infrastructure and Kubernetes metrics
• Open Source & Vendor-Neutral: No proprietary formats or lock-in
• Highly Customizable Dashboards: Grafana dashboards rival and often exceed Datadog’s visualization flexibility
• Large Ecosystem: Thousands of exporters, plugins, and integrations
• Cloud or Self-Hosted: Full control over data and deployment
• Widely Adopted: Strong community support and battle-tested at scale

Grafana Stack Cons:

• Not a single unified product like Datadog
• Requires managing multiple systems (Prometheus, Loki, Tempo)
• Operational overhead increases significantly at scale
• Alerting configuration is more complex than Datadog monitors

Integration / Mitigation:

• OpenTelemetry Collector can replace Datadog agents
• Can be adopted incrementally (metrics first, logs later)
• Grafana Cloud offers a managed path for teams leaving Datadog SaaS
• Often paired with managed storage backends for scale

3. New Relic

New Relic is one of the closest SaaS-based Datadog alternatives, offering a familiar all-in-one observability experience with strong APM and developer tooling.

New Relic Pros:

• Very Similar to Datadog UX: Easy transition for teams already using Datadog
• Strong APM Capabilities: Deep code-level performance insights
• Unified Observability: Metrics, logs, traces, RUM, and synthetics in one platform
• OpenTelemetry Support: Easier migration from Datadog agents
• Developer-Friendly: Good documentation and onboarding

New Relic Cons:

• Still a proprietary SaaS platform
• Costs can grow quickly with high data volume
• Less control over data residency than self-hosted tools
• Advanced features gated behind higher pricing tiers

Integration / Mitigation:

• Supports OpenTelemetry for vendor-neutral ingestion
• Migration tooling available from Datadog
• Suitable for teams wanting minimal operational change

4. Dynatrace

Dynatrace is an enterprise-grade Datadog alternative focused on automated instrumentation, AI-driven insights, and large-scale environments.

Dynatrace Pros:

• Automatic Instrumentation: Minimal manual setup compared to Datadog
• Strong APM & Root Cause Analysis: Davis AI reduces alert noise
• Enterprise-Ready: Handles very large, complex systems
• Hybrid & On-Prem Support: Suitable for regulated environments
• End-to-End Visibility: Infra to user experience

Dynatrace Cons:

• Premium pricing, often higher than Datadog
• Less flexible than open source alternatives
• Proprietary agents and data formats
• Overkill for smaller or cloud-native teams

Integration / Mitigation:

• OneAgent simplifies migration from Datadog agents
• OpenTelemetry supported for partial vendor neutrality
• Best suited for enterprises replacing Datadog at scale

5. Elastic Observability (ELK Stack)

Elastic Observability is a well-known Datadog alternative for teams heavily focused on log analytics and search-driven observability.

Elastic Observability Pros:

• Powerful Log Search: Elasticsearch excels at full-text and structured search
• Unified Logs, Metrics, and APM: Covers most Datadog use cases
• Flexible Deployment: Cloud, self-hosted, or hybrid
• Mature Ecosystem: Large community and integrations
• Security + Observability: Strong SIEM overlap

Elastic Observability Cons:

• Expensive to operate at scale
• High infrastructure and tuning overhead
• Storage costs grow quickly
• Complex cluster management compared to Datadog SaaS

Integration / Mitigation:

• Supports OpenTelemetry ingestion
• Beats and Logstash ease Datadog log migration
• Managed Elastic Cloud reduces operational burden

6. Splunk

Splunk is a long-standing Datadog alternative known for enterprise-grade log analytics, security, and compliance use cases.

Splunk Pros:

• Extremely Powerful Analytics: SPL enables deep correlation
• Enterprise-Grade Security: Strong compliance and audit capabilities
• Mature Platform: Proven reliability at massive scale
• On-Prem & Cloud Options: Flexible deployment models

Splunk Cons:

• One of the most expensive tools on the market
• Complex pricing and licensing
• Steep learning curve
• Often excessive for pure observability needs

Integration / Mitigation:

• Universal Forwarders simplify migration
• OpenTelemetry support improving
• Often used alongside other observability tools

7. Honeycomb

Honeycomb is a modern Datadog alternative focused on high-cardinality observability and debugging distributed systems.

Honeycomb Pros:

• Excellent for Microservices Debugging: Purpose-built for tracing and understanding complex request flows across distributed microservices.
• High-Cardinality Friendly: Handles high-cardinality dimensions (like user IDs and request IDs) without performance or cost blowups.
• Fast Exploratory Queries: Enables rapid, ad-hoc querying to investigate unknown issues in production.
• Strong SLO & Burn Rate Workflows: Provides first-class SLOs, error budgets, and burn-rate alerts tied to real request data.
• Developer-Centric Experience: Designed around developer and SRE workflows rather than infrastructure-only monitoring.

Honeycomb Cons:

• SaaS-only (no self-hosted option)
• Less focus on traditional dashboards
• Pricing scales with event volume
• Different mental model than Datadog

Integration / Mitigation:

• OpenTelemetry-native ingestion
• Can replace Datadog APM selectively
• Often used alongside infra monitoring tools

8. AppDynamics (Cisco)

AppDynamics is an enterprise APM-focused Datadog alternative, particularly strong for business transaction monitoring.

AppDynamics Pros:

• Deep Application Performance Monitoring: Provides detailed code-level visibility into application performance and dependencies.
• Business Transaction Visibility: Maps technical performance directly to business transactions and user impact.
• Tight Cisco Ecosystem Integration: Seamlessly integrates with Cisco networking, security, and enterprise tooling.
• Hybrid & Legacy System Friendly: Works well across on-prem, hybrid, and legacy enterprise environments.
• AI-Powered Root Cause Analysis: Uses the Cognition Engine to automatically correlate anomalies and identify probable root causes.

AppDynamics Cons:

• Expensive enterprise pricing
• Heavy agent-based approach
• Less cloud-native than Datadog

Integration / Mitigation:

• Agent-based migration from Datadog APM
• OpenTelemetry support improving
• Best for enterprises prioritizing APM over infra metrics

9. Zabbix

Zabbix is an open-source Datadog alternative for infrastructure monitoring, particularly popular in on-prem and hybrid environments.

Zabbix Pros:

• Completely Free & Open Source: Fully open-source with no licensing costs or feature gating.
• Excellent Host & Network Monitoring: Strong at monitoring servers, networks, and traditional infrastructure.
• Strong Alerting and Escalations: Offers robust alerting rules with flexible escalation policies.
• Predictable Costs: Self-hosted model ensures stable and predictable operational costs.
• Very Stable and Mature: Battle-tested platform with years of production use in enterprise environments.

Zabbix Cons:

• Not a full Datadog replacement for APM or tracing
• Limited native log analytics
• UI feels dated
• Not OpenTelemetry-native

Integration / Mitigation:

• Often paired with Grafana for dashboards
• Can coexist with OpenTelemetry-based tools
• Best used as infra monitoring layer

10. Uptrace

Uptrace is an OpenTelemetry-native Datadog alternative focused on tracing and lightweight APM.

Uptrace Pros:

• Built for OpenTelemetry from Day One: Native OpenTelemetry support for traces, metrics, and logs without adapters.
• Excellent Tracing Performance: Fast trace ingestion and querying optimized for distributed systems.
• Cost-Effective ClickHouse Backend: Uses ClickHouse for efficient storage and high-performance analytics at lower cost.
• Self-Hosted or Cloud: Flexible deployment options to run it yourself or use managed Uptrace Cloud.
• Simple and Clean UI: Minimal, intuitive interface focused on tracing and debugging workflows.

Uptrace Cons:

• Smaller ecosystem
• Less mature alerting than Datadog
• Limited enterprise features
• Narrower scope than full observability platforms

Integration / Mitigation:

• Seamless Datadog APM replacement via OpenTelemetry
• Docker and Kubernetes friendly
• Often paired with separate metrics/log tools

Comparison Table: Datadog Alternatives 2025

Tool	Deployment	Metrics	Logs	Traces	Pricing Model	Why Teams Choose It Over Datadog	Migration Ease
OpenObserve	Self-hosted / Cloud	✅	✅	✅	Open Source + Low-cost Cloud	Datadog-like unified observability without usage-based pricing or lock-in	⭐⭐⭐⭐⭐ (OTel-native)
Grafana Stack	Self-hosted / Cloud	✅	✅	✅	OSS + Managed	Replace Datadog with modular, open tooling	⭐⭐⭐⭐ (Multiple components)
New Relic	SaaS	✅	✅	✅	Usage-based SaaS	Familiar APM UX, easier switch for Datadog users	⭐⭐⭐⭐⭐ (Similar model)
Dynatrace	SaaS / Hybrid	✅	✅	✅	Host / Unit-based	Enterprise-grade automation Datadog lacks	⭐⭐⭐⭐ (Auto-instrumentation)
Elastic Observability	Self-hosted / Cloud	✅	✅	✅	Data / Host-based	Strong search-first alternative to Datadog logs	⭐⭐⭐ (More ops work)
Splunk Observability	SaaS / On-prem	✅	✅	✅	Data-volume based	Compliance-heavy, security-focused environments	⭐⭐⭐ (Different data model)
Honeycomb	SaaS	⚠️	⚠️	✅	Event-based	Better high-cardinality tracing than Datadog	⭐⭐⭐⭐⭐ (OTel-native)
AppDynamics	SaaS / On-prem	✅	✅	✅	Unit-based	Legacy enterprise Datadog replacement	⭐⭐⭐ (Agent-heavy)
Uptrace	Self-hosted / Cloud	✅	✅	✅	Open Source + Cloud	Lightweight Datadog-style APM at lower cost	⭐⭐⭐⭐⭐ (OTel-native)

How to Choose the Right Datadog Alternative

Selecting the right Datadog alternative depends on several factors:

1. Budget Constraints

• Tight budget? Consider open source: OpenObserve, Grafana Stack
• Moderate budget? New Relic or managed Grafana Cloud
• Enterprise budget? Dynatrace, AppDynamics, or Splunk

2. Deployment Preference

• Self-hosted required? OpenObserve, Grafana Stack, Elastic
• SaaS preferred? New Relic, Honeycomb, Dynatrace
• Hybrid needed? Dynatrace, Elastic, AppDynamics

3. Technical Expertise

• Strong ops team? Open source options offer maximum flexibility
• Limited resources? Managed SaaS solutions reduce operational burden
• Developer-focused? Honeycomb, OpenObserve

4. Primary Use Case

• General observability: OpenObserve, New Relic, Grafana Stack
• APM-focused: Dynatrace, AppDynamics, New Relic
• Log analytics: Elastic, Splunk, OpenObserve
• Distributed tracing: Honeycomb, Uptrace, OpenObserve
• Security + observability: Splunk, Elastic

5. Migration Strategy

• Quick migration: Choose OpenTelemetry-native tools (OpenObserve, Honeycomb)
• Gradual transition: Start with one signal type (logs or metrics)
• Parallel running: Run new tool alongside Datadog during evaluation

6. Scale Requirements

• Small to medium: Most options will work; prioritize ease of use
• Large scale: Consider OpenObserve, Grafana Stack, or enterprise platforms
• High cardinality: Honeycomb, OpenObserve, or ClickHouse-based solutions

Migrating from Datadog to OpenObserve

Migrating from Datadog to OpenObserve can be done incrementally using OpenTelemetry, without rewriting your existing instrumentation. By routing Datadog metrics through the OpenTelemetry Collector, teams can standardize on OTLP while gaining full control over data, costs, and storage. This approach allows you to run Datadog and OpenObserve side by side during migration, validate metrics parity, and gradually transition dashboards and alerts—all while avoiding vendor lock-in.

Read the full walkthrough here: Migrating from Datadog to OpenObserve

Conclusion

While Datadog is a powerful observability platform, various alternatives can better suit specific needs, budgets, and technical requirements.

• OpenObserve stands out for teams wanting unified observability with massive cost savings and the flexibility of open source
• Open source options (OpenObserve, Grafana Stack, Uptrace) provide maximum control and transparency
• SaaS alternatives (OpenObserve Cloud, New Relic, Dynatrace, Honeycomb) offer easier operation with different pricing models
• OpenTelemetry adoption makes migration significantly easier and prevents future vendor lock-in
• Start small: Pilot with non-critical services before full migration

The right choice depends on your team's specific needs, technical expertise, budget constraints, and long-term observability strategy. Many teams find that modern alternatives not only save costs but also provide better performance, more flexibility, and features specifically designed for cloud-native architectures.

Take the Next Step

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