Top 7 Jaeger Alternatives in 2025: Features, Pricing and Comparison

Jaeger is valued for its robust distributed tracing and strong OpenTelemetry (OTEL) integration, especially in microservices and Kubernetes environments. However, its tracing-only scope limits full MELT observability and real-time alerting. With the observability market projected to exceed $6.94 billion by 2034, teams are moving to platforms offering unified telemetry, smart sampling, and predictable costs.

CubeAPM stands out as the best Jaeger alternative by offering full MELT support, smart sampling, and flat, transparent pricing. It combines traces, logs, metrics, synthetics, and RUM in one OTEL-native platform—available in both SaaS and self-hosted models. With 60%+ cost savings, CubeAPM delivers enterprise-grade observability without the Jaeger overhead.

In this article, we’ll explore the top 7 Jaeger alternatives—starting with CubeAPM—evaluating each on observability coverage, pricing, OTEL support, deployment flexibility, and real-world performance.

APM Tools Comparison

Tool	Telemetry Support (OTEL)	Deployment (Self-host, Setup)	Pricing	Sampling Strategy
CubeAPM	✅	Self-hosted, setup <1 hr	Ingestion-based pricing of $0.15/GB	Smart Sampling
SolarWinds	✅	SaaS & Self-hosted Deployment	Modular pricing model: Monitoring and Observability $6/node / month Database $117/database/ month	Tail based sampling
Dynatrace	Limited OTEL	Partial on-prem	$0.08/hour per 8 GiB host (~$57.60/host/month)	Davis AI
Datadog	Limited OTEL	Cloud-only, setup in 1–2 hours	APM: starts at $31/host/month; logs - $0.1/GB + $1.7/M events (15d)	Head-based
Uptrace	✅	SaaS & On-prem; Docker, OTEL collector setup	Free plan with limited retention. Traces: $0.30–$0.50/GB depending on plan Metrics: $0.10 per million samples Logs: Not a core component	Full control via OTEL sampling policies
Splunk AppDynamics	❌	Enterprise on-prem, complex setup	ranges $6/month-$50/host/month, billed annually	Basic agent-level sampling
New Relic	Limited OTEL	Cloud-only,	Free tier✅ Ingestion based pricing of $0.35/GB + $400/user/month for full access	Head-based
Betterstack	❌	SaaS; easy setup, lightweight config	Free tier:✅. Logs: $0.25/GB beyond 1 GB/day No native support for metrics or traces	Sampling not applicable (logs only)

Top 7 AppSignal Alternatives

1. CubeAPM
2. Datadog
3. Dynatrace
4. Coralogix
5. New Relic
6. Zenoss
7. Lumigo

Why Look for Jaeger Alternatives?

Despite its open-source flexibility and low cost, Jaeger has several key limitations that prompt organizations to seek more complete and efficient alternatives:

1. Limited Observability Scope (Traces Only)

Jaeger only supports tracing. It lacks built-in support for logs, metrics, synthetics, and RUM, making it unsuitable as a standalone observability platform.

2. No Native Smart Sampling

Sampling in Jaeger is mostly head-based and static, which limits its efficiency in high-volume environments. It can miss tail-end anomalies and over-sample trivial transactions.

3. Complex Self-Hosting Requirements

Deploying and scaling Jaeger requires managing several components (agent, collector, ingester, query service, storage), which adds operational burden—especially without a managed option.

4. Lack of Full MELT & Alerting Integration

Jaeger does not provide event-based alerting, error tracking dashboards, or synthetic test capabilities, all of which are critical for incident response in modern environments.

5. Fragmented UI and Poor Query UX

While functional, the user experience is often cited as unintuitive, especially for non-tracing experts trying to correlate insights across different systems.

Criteria for Suggesting Jaeger Alternatives

To recommend strong Jaeger alternatives, we evaluated tools based on the following seven criteria:

1. Full MELT Support

We prioritized platforms that natively support Metrics, Events, Logs, and Traces to ensure comprehensive observability.

2. OpenTelemetry-First Architecture

The alternative should integrate natively with OpenTelemetry, without requiring proprietary agents or instrumentation rewrites.

3. Smart & Contextual Sampling

We favored tools that implement tail-based or dynamic sampling, helping teams retain valuable traces while cutting ingestion and storage costs.

4. Predictable and Transparent Pricing

Jaeger is open-source and free—but many teams face cost creep when pairing it with external backends. We included vendors with transparent, usage-based pricing or flat rates.

5. Deployment Flexibility (SaaS & Self-hosted)

Given Jaeger’s appeal in air-gapped and compliance-sensitive environments, we included only those tools that offer both self-hosted and SaaS deployment options.

6. Low-Latency Ingestion + Query Performance

High cardinality telemetry data requires fast pipelines. We included platforms that offer low ingestion latency and real-time querying without lag.

7. Integrated Alerting, Dashboards & Collaboration

Beyond tracing, we emphasized platforms that integrate with alerting, error tracking, dashboards, and incident collaboration workflows.

Jaeger Overview

Known for (Primary use case):

Jaeger is an open-source distributed tracing platform used to monitor microservices-based architectures. It’s widely adopted for visualizing request flows, identifying performance bottlenecks, and debugging latency issues.

Standout Features:

• Deep OpenTelemetry (OTEL) integration
• Scalable architecture supporting multiple storage backends like Elasticsearch and Cassandra
• Powerful trace visualizations and service dependency graphs
  

Key Features:

• End-to-end request tracing across distributed systems
• Service maps and trace metrics for root-cause analysis
• Supports both OpenTracing and OpenTelemetry APIs
• Backend-agnostic with options for memory, Cassandra, Elasticsearch
• UI built for trace filtering, span inspection, and timeline views
  

Pros:

• 100% open-source and free to use
• High flexibility and customizability for self-hosted environments
• Proven stability at scale in production (e.g., Uber’s internal usage)
• Strong OTEL compatibility for modern observability pipelines
  

Cons:

• Focused only on tracing—no native support for metrics, logs, alerts, or dashboards
• No built-in smart sampling or anomaly-based retention
• UI can be unintuitive without broader observability context
• Requires manual setup and significant DevOps effort to scale

Best for:

Engineering teams looking for a dedicated, vendor-neutral tracing system with full control over deployment and cost. Suitable for organizations that already have separate systems for metrics, logs, and alerting.

Pricing & Customer Reviews:

• Pricing: Jaeger is completely open-source with zero licensing cost. However, infrastructure, maintenance, and operational expenses are borne by the user.
• Customer Rating: Rated 4.4/5 on G2. Users appreciate its strong tracing capabilities and OTEL integration but cite its limited scope and steep learning curve as drawbacks.

Top 7 Jaeger Alternatives

1. CubeAPM

Known for (Primary use case):

CubeAPM is an OpenTelemetry-native observability platform offering full-stack APM across metrics, events, logs, and traces (MELT). It’s built for high-performance environments that demand cost-efficiency, compliance-friendly deployments, and seamless OTEL compatibility.

Key Features:

Full MELT Stack Coverage
CubeAPM supports logs, metrics, traces, errors, synthetics, and RUM in a unified platform—eliminating the need to stitch together multiple tools.

Smart Sampling Engine
Unlike Jaeger’s head-based sampling, CubeAPM uses contextual sampling that retains high-value traces (e.g., high latency, errors) while discarding noise, reducing data volumes by over 70%.

Self-Hosted & SaaS Deployment
Deploy in your own cloud or opt for managed SaaS—CubeAPM supports both models, offering flexibility for compliance and data localization.

Fast Ingestion & Query Performance
Optimized for low-latency telemetry pipelines, CubeAPM offers near-instant trace querying, even at scale.

High Compatibility
Works out of the box with OTEL agents, Prometheus exporters, Datadog, New Relic, and Elastic instrumentation—ideal for teams migrating from existing stacks.

Standout Features:

• Flat-rate pricing at $0.15/GB with no per-host or per-user fees
• Real-time trace filtering with intelligent retention
• On-prem storage that saves on cloud egress and meets data residency requirements
• Slack/WhatsApp-based support with minute-level response times
  

Pros:

• Unified observability with full MELT support
• Transparent, low-cost pricing model (60–70% cheaper than Datadog/New Relic)
• Native OTEL support and fast time-to-value
• Real-time alerting, dashboards, and integrations built in
  

Cons:

• UI may feel unfamiliar to teams coming from legacy tools
• Limited marketplace for prebuilt dashboards compared to older platforms

Best for:

Teams seeking cost-effective, OpenTelemetry-native observability with full-stack support and deployment control—especially for regulated industries or high-volume telemetry pipelines.

Pricing & Customer Reviews:

• Pricing: Starts at $0.15/GB with additional infra costs at $0.02/GB. No per-host, per-user, or data retention fees.
•  Rating: 4.7/5 (Based on Slack and User feedback).
  

CubeAPM vs Jaeger:

While Jaeger provides solid distributed tracing, CubeAPM delivers full-stack observability with smart sampling, flat pricing, and real-time MELT capabilities. For teams needing more than just traces—without the overhead of managing multiple tools—CubeAPM is a major upgrade over Jaeger.

2. Datadog

Known for (Primary use case):

Datadog is a cloud-native observability platform offering infrastructure monitoring, APM, log management, security, and RUM—all under one unified dashboard. It’s widely adopted in enterprise DevOps teams for its deep integrations and wide telemetry coverage.

Key Features:

Modular MELT Coverage
Datadog supports metrics, events, logs, and traces, along with RUM, synthetics, CI visibility, and more—though most features are sold as add-ons.

900+ Integrations
Out-of-the-box integrations with AWS, GCP, Azure, Kubernetes, Docker, and nearly every modern tool in the stack.

Dashboards & Alerts
Highly customizable dashboards, anomaly detection, and SLO-based alerting across services and environments.

Live Search & Log Indexing
Real-time log exploration with filters, saved views, and long-term log retention—at additional cost.

Standout Features:

• 15+ observability modules in one UI
• Unified correlation across metrics, traces, logs, and events
• Extensive ecosystem of prebuilt integrations
• Fast UI and detailed service maps
  

Pros:

• Comprehensive all-in-one observability suite
• Mature ecosystem and integrations
• Enterprise-ready dashboards and alerting
• Global presence with multi-region data ingestion
  

Cons:

• Complex and unpredictable pricing structure
• High-cardinality data incurs large costs
• High-water mark billing penalizes scaling
• Smart sampling is limited to head-based or static strategies
  

Best for:

Large teams with generous observability budgets looking for turnkey solutions across MELT, security, and DevOps workflows.

Pricing & Customer Reviews:

• Pricing:
  • APM: starts at $31/host/month; 
  • logs – Effective Cost: $0.1/GB + $1.7/M events (15d), synthetics billed separately; 
  • Infra Cost; starting at $15/host/month
• Rating: 4.3/5 (G2)
  

Datadog vs Jaeger:

Datadog offers much broader observability than Jaeger but comes at a high and often unpredictable cost. While Jaeger is focused and open-source, Datadog bundles multiple tools with deep integrations—but charges heavily for each feature and data volume spike.

3. Dynatrace

Known for (Primary use case):

Dynatrace is an enterprise-grade observability and application intelligence platform. It’s widely used for performance monitoring, auto-discovery, and full-stack observability in large-scale dynamic environments.

Key Features:

Davis AI Engine
Dynatrace’s proprietary AI, Davis, continuously analyzes dependencies and telemetry to detect anomalies and auto-triage root causes in real time.

Auto-Instrumentation & Service Discovery
Dynatrace agents automatically instrument code, discover services, and map dependencies—reducing manual setup time significantly.

Full MELT Observability
Supports metrics, events, logs, and traces, as well as session replay, RUM, Kubernetes monitoring, and synthetic checks in a single platform.

Infrastructure + Application Monitoring
From host-level health to fine-grained code execution, Dynatrace provides deep visibility across the entire stack—cloud, containers, functions, VMs, and apps.

Standout Features:

• OneAgent for auto-instrumentation
• Davis AI for real-time root-cause analysis
• End-to-end visibility without stitching multiple tools
• Smart baselining and anomaly detection
  

Pros:

• Extremely powerful for large, dynamic environments
• High automation with minimal manual instrumentation
• Excellent for enterprise observability and AIOps use cases
• Rich visualizations and dependency maps
  

Cons:

• High cost, especially at scale
• Limited self-hosting options
• Learning curve for advanced configuration
• Heavy agent footprint in some environments
  

Best for:

Enterprises with complex, hybrid environments that need automated insights, full-stack monitoring, and AI-driven anomaly detection.

Pricing & Customer Reviews:

• Pricing: $0.08/hour per 8 GiB host (~$57.60/host/month)
• Rating: 4.4/5 (G2)
  

Dynatrace vs Jaeger:

Dynatrace offers vastly more automation and breadth than Jaeger—but it comes with a high price tag and heavier setup. While Jaeger is ideal for focused tracing, Dynatrace appeals to enterprises needing full-stack insights with minimal instrumentation effort.

4. Coralogix

Known for (Primary use case):

Coralogix is a telemetry data pipeline platform that enables teams to monitor logs, metrics, and traces with fine-tuned control over cost and retention. It’s known for its unique log lifecycle management model and powerful indexing controls.

Key Features:

Log Lifecycle Management
Coralogix categorizes log data into different processing tiers—Real-time, Frequent, Infrequent, and Archive—allowing cost optimization by limiting indexing only to what’s necessary.

Full MELT Stack Support
Supports logs, metrics, traces, alerts, and dashboards. It also provides CI/CD monitoring and integrations with cloud-native tools like AWS, Kubernetes, and Terraform.

Data Stream to Own Cloud
Archived data is stored in the customer’s own S3 or GCS bucket, drastically reducing long-term storage costs compared to SaaS-only models.

Dynamic Alerting
Supports JSON-based queries, custom conditions, and dynamic thresholds to build precise and contextual alerts.

Standout Features:

• Tiered log ingestion and indexing to control cost
• Customer-owned storage for long-term archival
• Supports OpenTelemetry and fluent-bit agents
• Real-time observability with ingestion-to-alert latency under 1 minute
  

Pros:

• Very flexible pricing based on data lifecycle
• Allows customers to retain large volumes of logs affordably
• Native support for OTEL, fluent-bit, and standard exporters
• Offers private SaaS and self-hosted deployment options
  

Cons:

• Data still flows through Coralogix before archival, incurring egress fees
• Not fully compliant with data localization in some regulated industries
• Interface can be complex for new users
• Sampling logic not as intelligent as tail-based engines
  

Best for:

Organizations ingesting large volumes of logs and traces who need to reduce costs through smart routing, and those that want partial data ownership while still using a SaaS UI.

Pricing & Customer Reviews:

• Pricing
  • Logs: $0.52/GB, infinite retention
  • Traces: $0.44/GB, infinite retention
  • Metrics:$0.05/GB, infinite retention
  • AI: 1.5 per 1M tokens
• Rating: 4.5/5 (G2)
  

Coralogix vs Jaeger:

Coralogix provides broader observability and lifecycle control compared to Jaeger, which is limited to traces. However, teams needing full data sovereignty and OTEL-native pipelines may still prefer alternatives that offer true self-hosting or better compliance flexibility.

5. New Relic

Known for (Primary use case):

New Relic is a full-stack observability platform offering performance monitoring, infrastructure visibility, log management, and user experience monitoring—all under a unified pricing model.

Key Features:

All-in-One Telemetry Platform
Provides metrics, events, logs, and traces (MELT) with support for frontend, backend, and infrastructure monitoring in a single interface.

Infinite Tracing
Offers distributed tracing with no sampling limit at ingestion—although pricing makes full retention expensive at scale.

Telemetry Data Platform (TDP)
Centralized ingestion and querying engine with support for custom dashboards, alerts, and AI-assisted issue detection.

OpenTelemetry Integration
New Relic supports OTEL instrumentation but often requires translation or agent shims for full compatibility.

Standout Features:

• Unified UI for full-stack observability
• NRQL query language for custom dashboards and alerts
• Browser monitoring, mobile performance, and Synthetics included
• Alerts tied to golden signals and SLIs
  

Pros:

• Full MELT coverage in a single UI
• Prebuilt integrations for AWS, Kubernetes, and major frameworks
• Fast setup with auto-instrumentation for many languages
• Real-time performance insights and customizable dashboards
  

Cons:

• High cost per user and data ingested
• OTEL support is partial and often needs adaptation
• Vendor-hosted only—no self-hosting
• Long-term retention and high cardinality data pricing adds up quickly
  

Best for:

Midsize to large teams looking for an all-in-one platform with quick onboarding, full-stack support, and high dashboarding flexibility.

Pricing & Customer Reviews:

• Pricing: 
  • Free: 100 GB/month of data ingest
  • Starts at $0.35/GB for telemetry + $400/user/month for full feature access
• Rating: 4.4/5 (G2)
  

New Relic vs Jaeger:

New Relic offers far more functionality than Jaeger but at a steep cost. While Jaeger is better for teams wanting full control over self-hosted tracing, New Relic appeals to teams that want a quick-to-deploy SaaS platform—if budget isn’t a major constraint.

6. Zenoss

Known for (Primary use case):

Zenoss is known for hybrid IT monitoring, primarily focused on infrastructure, network, and application health across on-premise and cloud environments. It’s often used in large enterprises for unified visibility into physical and virtual assets.

Key Features:

Hybrid Infrastructure Monitoring
Zenoss tracks the availability and performance of servers, network devices, storage, VMs, and cloud resources in a single platform.

Service Modeling & Dependency Mapping
Provides real-time service modeling to visualize and monitor dependencies between infrastructure components and applications.

Zenoss Cloud
Their SaaS offering provides predictive analytics, telemetry collection, and anomaly detection across large-scale distributed systems.

Extensibility via ZenPacks
Modular ZenPacks add custom monitoring capabilities for various technologies, from databases and hypervisors to SNMP-based devices.

Standout Features:

• Unified monitoring for hybrid environments (on-prem, virtual, cloud)
• Dependency-aware alerting and intelligent root cause analysis
• Customizable through ZenPacks ecosystem
• Integration with ITSM tools for incident workflows
  

Pros:

• Strong infrastructure and network monitoring capabilities
• Scalable to large enterprise environments
• Offers both on-premise and cloud-hosted deployments
• Useful for data center and NOC-style visibility
  

Cons:

• Limited support for modern observability stacks like OpenTelemetry
• No built-in support for distributed tracing or advanced APM
• Complex UI and setup compared to newer tools
• Custom ZenPacks may require development effort and maintenance
  

Best for:

Large enterprises with hybrid or legacy infrastructure needing deep visibility into networks, physical hardware, and virtualization layers—not ideal for cloud-native, trace-centric environments.

Pricing & Customer Reviews:

• Pricing: Not publicly listed; enterprise contracts based on monitored endpoints and features
• Rating: 4.2/5 (G2)
  

Zenoss vs Jaeger:

Zenoss and Jaeger serve entirely different use cases—while Jaeger excels at tracing in microservices, Zenoss focuses on infrastructure monitoring at the device and network level. Teams needing application-level observability will find Jaeger more useful, while Zenoss suits traditional IT environments.

7. Lumigo

Known for (Primary use case):

Lumigo is a serverless and container-native observability platform built specifically for debugging and monitoring distributed applications, especially in AWS Lambda and microservices environments.

Key Features:

Serverless Tracing
Offers auto-instrumented distributed tracing for AWS Lambda, ECS, Fargate, and containers without modifying code—designed for low-code/no-code monitoring.

End-to-End Debugging
Tracks every request across functions, services, and APIs with full visibility into payloads, logs, and response times.

Issue Correlation Engine
Automatically correlates logs, metrics, and traces to identify root causes and affected services within microservice environments.

Real-Time Visual Maps
Interactive service maps visualize the call graph and dependencies in real time, helping users detect latency spikes or failing services quickly.

Standout Features:

• Purpose-built for serverless and microservice environments
• Seamless AWS integration with zero-code tracing setup
• Automated root-cause detection across traces and logs
• Granular request-level visibility for debugging asynchronous flows
  

Pros:

• Very fast to deploy and start tracing in serverless stacks
• Lightweight with minimal performance overhead
• Integrates natively with AWS services (Lambda, SQS, DynamoDB, etc.)
• Excellent for request flow tracking and debugging across APIs
  

Cons:

• Primarily focused on AWS—limited multi-cloud support
• No native infrastructure monitoring
• MELT coverage is partial—heavier focus on traces/logs, weaker on metrics
• SaaS only—no self-hosting or air-gapped deployment option
  

Best for:

Teams running AWS Lambda or containerized microservices who need fast, zero-code distributed tracing with debugging workflows built in.

Pricing & Customer Reviews:

• Pricing
• Basic Free includes 150k Traces and 14-day Trace retention
• Standard: $99/month; 1M races, 14 day trace retention
• Plus:$299/month; 5M traces and 14 day trace retention
• Rating: 4.6/5 (G2)
  

Lumigo vs Jaeger:

While Jaeger is better suited for self-hosted, customizable tracing in Kubernetes environments, Lumigo shines in serverless-first AWS ecosystems. It offers deeper out-of-the-box integrations, faster setup, and built-in debugging—but lacks the deployment flexibility and extensibility of Jaeger.

Conclusion

While Jaeger remains a solid open-source tool for distributed tracing, its limited scope and lack of built-in MELT support make it less viable as a standalone observability solution for modern, fast-moving teams. As organizations increasingly adopt OpenTelemetry, demand real-time alerting, and aim for cost-efficient full-stack visibility, Jaeger’s tracing-only approach and operational overhead can become a bottleneck.

Tools like CubeAPM, Dynatrace, Coralogix, and Lumigo offer broader capabilities, smarter sampling, and more deployment flexibility—without sacrificing depth or performance. Whether you’re looking to reduce costs, improve compliance, or consolidate your observability stack, these Jaeger alternatives provide strong options tailored for today’s cloud-native and serverless environments.