10 Best OpenTelemetry Tools in 2024

Imagine launching your app only to encounter performance bottlenecks or elusive errors that went unnoticed. OpenTelemetry provides a standardized approach to collecting essential telemetry data—spanning metrics, traces, and logs—from your application.

However, capturing data is only the first step. You need a reliable backend to process, analyze, and visualize this information to gain meaningful insights and maintain optimal performance. With so many options, choosing the right OpenTelemetry backend can feel daunting.

This article compiles the top 10 OpenTelemetry backend tools designed to simplify observability.

Why use an OpenTelemetry backend tool?

You gain access to rich telemetry data when you instrument your app with OpenTelemetry. However, without a backend to ingest, store, and analyze it, this data is like scattered puzzle pieces without a reference image.

OpenTelemetry backend tools provide a centralized platform to process distributed traces, logs, and metrics. These tools deliver actionable insights, helping you identify performance bottlenecks, uncover root causes, and monitor the health of your entire stack in real-time.

Factors to consider when choosing an OpenTelemetry tool

To simplify the decision-making process, here are five critical factors to evaluate and examples to illustrate their importance.

Native compatibility with OpenTelemetry standards

Let's say your team has carefully instrumented your services using OpenTelemetry’s semantic conventions. If your chosen backend doesn’t natively support these standards, you risk losing essential context, such as custom attributes, making troubleshooting far more complex. A backend with native OpenTelemetry support ensures seamless data ingestion while preserving the details you’ve captured, saving time and reducing complexity.

Comprehensive support for logs, metrics, and traces

Observability depends on integrating logs, metrics, and traces to provide a complete view of your system's behavior. Without all three, you risk losing critical context.

For example, consider a scenario where your application is monitored by a backend that exclusively supports metrics. You might observe a spike in CPU usage but lack the traces needed to identify which specific microservice is causing the issue. This gap in visibility could lead to prolonged troubleshooting and delayed resolutions.

A backend that supports all three signals enables you to correlate logs (e.g., error messages), metrics (e.g., CPU spikes), and traces (e.g., request flows). This holistic approach empowers you to quickly pinpoint the root cause of issues and resolve them efficiently, minimizing downtime and ensuring a seamless user experience.

Scalability and efficient data storage

As your application traffic grows, so does the volume of telemetry data. A backend that cannot scale effectively will falter under this load, blinding you to performance issues during critical moments.

Choosing a tool built for large-scale data ingestion and storage, such as one that employs efficient storage engines and querying mechanisms, ensures you have uninterrupted, real-time insights into your system’s health.

Powerful querying and visualization capabilities

Data without actionable insights is just noise. A backend should offer powerful querying with intuitive syntax and tools that let you create custom dashboards, set alerts for anomalies, and visualize trends. For instance, if a batch of IoT sensors malfunctions in a specific region, a well-designed backend lets you spot the issue immediately and take corrective action before it impacts users.

Ease of deployment and strong community support

Whether you’re self-hosting or using a cloud-based solution, ease of deployment is crucial. A backend tool should be simple to set up, allowing you to focus on monitoring rather than configuration. Moreover, tools with active community support provide regular updates, extensive documentation, and forums for troubleshooting. This effectively extends your team with a wealth of shared knowledge and resources.

By considering these factors, you can choose an OpenTelemetry backend tool that aligns with your application's needs and ensures reliable, actionable observability.

1. Better Stack

Better Stack is an excellent OpenTelemetry backend that perfectly balances simplicity and robust features. Better Stack’s intuitive design lets you monitor, analyze, and troubleshoot your infrastructure—all within a single, cohesive platform.

Better Stack’s OpenTelemetry-native integration allows you to ingest logs and metrics effortlessly, turning raw telemetry data into actionable insights in seconds. While the platform’s distributed tracing capabilities are being developed, its existing log and metrics management tools already provide a solid foundation for comprehensive observability. It automatically structures logs into JSON formats, making searching through logs straightforward. With ClickHouse SQL integration, you can write queries for more in-depth analysis. Not comfortable with SQL? No problem—the built-in query builder creates queries for you, giving you the necessary insights.

Better Stack is proactive with its real-time monitoring and checks your servers, applications, and APIs every 30 seconds to ensure you receive accurate updates. If something goes wrong, you’re not just notified—you’re equipped with the full context, including detailed error logs, screenshots, and diagnostic data, allowing you to jump into resolution mode immediately.

Furthermore, Better Stack offers a comprehensive incident response. On-call scheduling and collaborative workflows make incident management more efficient, enabling your team to resolve outages quickly. It doesn’t stop there—Better Stack takes user communication to the next level with customizable status pages. Instead of leaving users in the dark, you can keep them informed in real-time, turning a potentially frustrating experience into a chance to demonstrate transparency and build trust.

🌟 Key features

• Infrastructure Monitoring
• Log and metrics management
• Incident management
• Website monitoring
• OpenTelemetry-native support

➕ Pros

• Offers drag-and-drop, SQL, and PromQL querying options
• Strong native OpenTelemetry support
• Customizable, multilingual, and feature-rich status pages
• Clean and user-friendly interface
• Slack-based workflows, AI incident silencing, and smart merging to reduce noise and accelerate response
• Iintegrations with AWS, Prometheus, Datadog, Slack, and more

➖ Cons

• Distributed tracing is currently in development but expected soon

💲 Pricing

Better Stack’s free plan provides ten monitors, 3 GB of log retention, and a status page—perfect for starting with minimal risk. The pay-as-you-go plan starts at $29/month, unlocking advanced features like unlimited alerts, extended log retention, and enhanced incident management. Tailored plans are available for enterprises, offering additional benefits such as AI-driven insights and priority support.

Learn more about pricing on the Better Stack pricing page.

2. New Relic

New Relic is another OpenTelemetry backend tool to consider for a suite of observability tools that bring clarity to complex systems. New Relic’s metric collection capabilities provide a comprehensive suite of observability tools that make managing complex systems feel straightforward. With real-time metrics collection supporting OpenTelemetry, Prometheus, and over 100 cloud services, New Relic lets you monitor your application's health from every angle.

Relic’s distributed tracing provides exceptional visibility into request flows within your application. Using infinite tracing with tail-based sampling, it captures only the most critical traces, filtering out noise to highlight performance bottlenecks. This approach ensures deep insights without overwhelming you with unnecessary data.

Logs are another area where New Relic shines. Its logs-in-context feature automatically correlates logs with traces and metrics, making it easy to diagnose issues without juggling multiple data sources. Real-time querying and centralized log storage offer deep insights that complement your metrics and traces, helping you resolve issues faster.

But that's not all! New Relic also provides synthetic monitoring, security features, and real user monitoring, giving you a complete picture of your application's health.

🌟 Key features

• Infrastructure monitoring
• Infinite Tracing
• W3C Trace Context support
• Real user monitoring
• Trace propagation
• Application performance monitoring
• Log management
• Head-based sampling
• Synthetic monitoring

➕ Pros

• OpenTelemetry integration for unified data collection
• Infinite tracing with tail-based sampling for deeper insights
• Logs-in-context for efficient root-cause analysis
• Integrations with 100+ cloud services
• Advanced Query capabilities via NRQL for custom dashboards and alerts

➖ Cons

• It has a proprietary query language (NRQL) that has a steep learning curve
• High costs for data ingestion and user access

💲 Pricing

You can get started with New Relic with its free tier that offers 100 GB of monthly data ingestion and full platform access for a single user, making it a great entry point if your team is small. For teams with higher data needs, pricing starts at $0.35 per GB on a pay-as-you-go model. Pro and enterprise plans offer advanced security, extended data retention, and dedicated support tailored for larger organizations with complex requirements.

3. Logz.io

If you seek an open-source-friendly observability solution, Logz.io offers an all-in-one platform for telemetry data. It integrates popular tools like Grafana, Prometheus, and Jaeger, providing a seamless experience for monitoring and troubleshooting your applications. Its strong OpenTelemetry integration makes it easy to collect telemetry data without the typical setup and maintenance complexity.

Logz.io’s distributed tracing delivers deep visibility into microservices, allowing you to quickly follow requests across your stack and pinpoint performance issues. The platform’s log management complements this by providing real-time insights and context for your trace data, while metrics monitoring offers a detailed view of your system’s performance trends.

With features like LogMetrics, which converts logs into efficient time-series metrics, and a data optimization hub to filter out unnecessary log data, Logz.io significantly reduces costs while enhancing analysis speed. This unified approach and real-time metrics monitoring provide a comprehensive view of your system’s health and performance trends.

🌟 Key features

• Log management
• Distributed tracing
• Metrics monitoring
• LogMetrics
• Data optimization hub
• Infrastructure monitoring
• Service maps and dependency visualization

➕ Pros

• Data Optimization Hub significantly reduces data volume and costs (up to 32% savings)
• Unified observability experience with correlated logs, metrics, and traces
• Scalable, fully managed log ingestion and storage with built-in security and compliance (SOC-2, HIPAA)
• Customizable dashboards and a reliable alerting system with support for Slack, Opsgenie, and PagerDuty
• Trace sampling wizard simplifies OpenTelemetry configuration, reducing setup complexity
• LogMetrics converts logs into cost-efficient metrics for trend analysis
• Archive & Restore offers cost-effective long-term storage with fast data retrieval

➖ Cons

• Documentation can be inconsistent and lacking in certain areas
• Limited customization for certain aspects of dashboards and query flexibility

💲 Pricing

Logz.io uses a flexible pricing model based on data volume and service type. The 14-day free trial allows you to explore the platform’s full capabilities. Log management starts at approximately $0.90 per GB, while custom plans for metrics and tracing begin at around $29 per month. Enterprise plans offer tailored pricing with advanced features, including extended telemetry retention and premium support.

4. Dynatrace

Dynatrace is another compelling choice for an OpenTelemetry backend because it delivers a fully unified observability platform that integrates metrics, logs, and traces in one place. Its real-time Smartscape map gives you an instant, automatic view of your entire system’s dependencies, making it easier to track issues as your environment evolves.

Dynatrace is also powered by the Davis AI engine, which detects anomalies, predicts problems, and provides fast, actionable insights without manual intervention. The platform’s OpenTelemetry integration, paired with automatic instrumentation from OneAgent, ensures you can gather comprehensive data effortlessly.

🌟 Key features

• Real user monitoring
• Log management
• Digital experience monitoring
• Application security
• Infrastructure and cloud monitoring
• Distributed tracing
• Synthetic monitoring

➕ Pros

• Offers automated topology mapping and end-to-end tracing without manual setup
• OneAgent automatically captures logs, metrics, and traces without manual configuration.
• AI capabilities automate anomaly detection and provide predictive alerts
• integration with hundreds of technologies and cloud services
• Real-time vulnerability detection

➖ Cons

• The platform’s extensive features can be overwhelming

💲 Pricing

Dynatrace’s offers pay-as-you-go model is designed to adapt to your needs, offering transparent pricing without surprises. Full-stack monitoring costs $0.08 per hour for an 8 GiB host, covering everything from distributed tracing to application and infrastructure insights. Infrastructure monitoring costs just $0.04 per hour for more straightforward requirements, regardless of host size. Specialized services like Kubernetes observability, log management, and advanced security features are priced separately, ensuring you only pay for the capabilities you use.

5. Datadog

Datadog is another tool that makes it a strong contender as an OpenTelemetry backend. Its native integration with OpenTelemetry enhances its ability to collect, correlate, and visualize telemetry data from diverse environments.

Datadog's core strength is its ability to provide complete visibility across the entire tech stack. It allows you to trace requests end-to-end, track application performance, and correlate metrics and traces in real-time. The auto-generated service overviews and visualizations help you understand the flow and dependencies of requests, making troubleshooting more efficient.

In addition, Datadog has a sophisticated alerting system that can notify users of issues at any scale—from a single host to an entire cluster. It supports complex alerting logic, integrates with multiple channels (Slack, PagerDuty, email), and allows for flexible muting during maintenance.

Further, Datadog’s dashboard capabilities are highly customizable, allowing you to create interactive and real-time visualizations of metrics and events. The ability to slice and dice data using tags, hosts, or custom attributes provides deep analytical power, making it easier to uncover performance issues and trends quickly.

🌟 Key features

• Infrastructure monitoring
• Application performance monitoring
• Log management
• Synthetic monitoring
• Real user monitoring
• Network performance monitoring

➕ Pros

• Unified view of metrics, traces, and logs for effective troubleshooting
• Out-of-the-box monitoring capabilities and automated setup for common use cases
• Comprehensive observability with APM, infrastructure monitoring, log management, and RUM
• User-friendly interface, making it easier to set up and use without extensive training
• Extensive integrations with over 800+ tools, cloud providers, and services
• Highly customizable dashboards for detailed data visualization

➖ Cons

• High costs and unpredictable billing make it challenging to plan budgets effectively.

💲 Pricing

Datadog has flexible plans tailored to fit your needs, whether you’re just starting out or running complex DevSecOps workflows:

• Free tier: Perfect for small projects, this plan covers up to 5 hosts with 1-day metric retention to get you started quickly
• Pro tier: At $15 per host/month (billed annually), you get 15-month metric retention, access to 800+ integrations, and customizable dashboards to visualize your data like a pro
• Enterprise tier: For $23 per host/month (billed annually), unlock advanced features like machine learning-based alerts and live process monitoring for deeper insights
• DevSecOps pro: Starting at $22 per host/month, this plan adds essential security features, including scanning for misconfigurations and container vulnerability management
• DevSecOps enterprise: From $34 per host/month, get comprehensive threat detection, cloud workload security, and advanced entitlement management for the ultimate peace of mind

6. Coralogix

Coralogix is designed to simplify data handling and enhance observability without the high costs of traditional indexing. Its Streama© technology processes logs, metrics, and traces directly from cloud storage without indexing, drastically reducing storage expenses while ensuring rapid data access.

The platform excels in data enrichment, automatically parsing telemetry and adding business and operational metadata, making analysis faster and more insightful. Coralogix’s querying capabilities are flexible and user-friendly, supporting Lucene, SQL, and the speedy DataPrime language, enabling you to extract valuable insights quickly.

The Events2Metrics feature further boosts efficiency by converting log events into metrics, reducing storage needs while preserving critical observability data. With customizable dashboards and integrations like Grafana and Kubernetes, users get rich visualizations tailored to their specific needs.

🌟 Key features

• Log, metrics, and trace management
• Dynamic alerting
• Application performance monitoring
• Security monitoring
• Synthetic and real user monitoring

➕ Pros

• Streama© technology reduces costs by analyzing data in-stream without indexing
• Intuitive UI and customizable dashboards simplify data visualization
• Strong integration with OpenTelemetry, supporting multiple SDKs and various data sources like AWS, Kubernetes, and serverless environments
• Comprehensive log, metric, and trace correlation simplifies troubleshooting and improves investigation efficiency
• Excellent customer support, offering responsive, real-time assistance and dedicated onboarding

➖ Cons

• Steep learning curve for the DataPrime query language
• Limited backend storage options

💲 Pricing

Coralogix’s pricing model is designed for flexibility, charging $1.15 per GB for frequent searches, $0.50 per GB for monitoring, and just $0.17 per GB for compliance storage. The built-in TCO Optimizer offers smart cost planning, helping you control your budget. You can start with a free trial, and if you need more, they provide custom pricing options for larger data volumes.

7. Splunk

Splunkis an excellent choice for an OpenTelemetry backend due to its comprehensive approach to observability, extensive feature set, and strong support for integration.

Splunk can ingest data from virtually any source using various input methods, including forwarders and the event collector API, simplifying onboarding data. This broad compatibility makes Splunk highly versatile for OpenTelemetry use cases, providing an easy way to bring in traces, logs, and metrics.

Splunk’s proprietary Search Processing Language (SPL) is a significant differentiator, offering deep analytical capabilities with over 140 commands, supporting complex correlations like transactions, time-series analysis, and machine learning methods. Moreover, Splunk provides various visualization options and customizable dashboards, allowing you to create compelling data stories and quickly identify issues.

🌟 Key features

• Synthetic API monitoring
  
• Log management
  
• Infrastructure monitoring
  
• Incident management
  
• Application performance monitoring
  

➕ Pros

• Splunk provides powerful data visualization capabilities
• Provides real-time alerts and notifications based on custom rules -Features predictive analytics and anomaly detection to aid in proactive monitoring and insights

➖ Cons

• The platform’s architecture can be difficult to learn High costs can be a massive barrier

💲 Pricing

Splunk offers flexible pricing for various monitoring needs, from basic infrastructure to full-stack observability. Here’s a quick breakdown of their pricing:

• Infrastructure monitoring: $15 per host/month
• Full observability (APM + RUM): $75 per host/month
• Application performance monitoring (APM): $55 per host/month
• Real user monitoring (RUM): $14 per 10,000 sessions
• Synthetic API monitoring: $1 per 10,000 requests
• Incident management: $5 per user/month
• Flexible pricing options: workload-based, data ingestion, or entity count

8. Honeycomb

Honeycomb is an observability platform that eliminates the traditional separation of logs, metrics, and traces. Unifying these data types into a single format allows you to query and analyze data from one user interface. This reduces context switching and provides a comprehensive view of system behavior, making it an excellent fit for OpenTelemetry.

Honeycomb not only supports OpenTelemetry but actively contributes to the project. It provides OpenTelemetry SDKs for popular languages, simplifying integration and making it easier for teams to send standardized telemetry data directly to Honeycomb.

Besides this, Honeycomb's powerful query engine and unique database architecture enable near-instantaneous querying, which is crucial for fast incident resolution. Using a query engine optimized for complex and high-cardinality queries allows you to explore data in ways that traditional logging or APM tools can’t.

To complement this, Honeycomb offers unique features like BubbleUp, which automatically surfaces anomalies by comparing every attribute across millions of requests. This automated comparison helps you pinpoint outliers quickly, enhancing root cause analysis. Another great feature is the service map, which visualizes system dependencies and interactions, enabling you to understand their architecture at a glance and ask targeted questions about specific components.

🌟 Key features

• Log management
• Service maps
• Distributed tracing
• Service level objective

➕ Pros

• Features like query annotations, team history, and persistent queries simplify collaboration
• Provides intelligent sampling to manage event volume and make debugging data more resource-efficient
• The BubbleUp feature automatically detects anomalies and highlights outliers in visualizations
• The intuitive UI and helpful guides make it easy to get started

➖ Cons

• Honeycomb does not perform aggregation or roll-ups for time series data, which may be a limitation if you need business-level metric reporting
• Does not support observability features like real user monitoring or live log tailing.

💲 Pricing

Honeycomb offers a free plan with up to 20 million monthly events, perfect for getting started and exploring its powerful features. If you need more, the pro plan begins at just $130 per month, covering up to 100 million events, with flexible scalability that can support up to 1.5 billion events. For more extensive or unique needs, custom pricing options are also available to fit your requirements.

9. Sumo Logic

Sumo Logic is a tool that intergrates OpenTelemetry as a core part of its observability strategy, emphasizing its role as a comprehensive, cloud-native framework for collecting telemetry data. Sumo logic also combines multiple aspects of monitoring, such as infrastructure security, cloud SIEM, log analytics, and application observability, into a single platform. The platform excels in handling large-scale data, boasting an average of 35TB daily log ingestion and analyzing up to 500,000 data points per minute.

Along with this, Sumo Logic provides out-of-the-box (OOTB) dashboards and analytics, allowing you to quickly pinpoint issues, identify recurring errors, and resolve underlying problems effectively. It has a query feature, which allows you to search through large datasets and correlate information quickly. The platform also integrates with a variety of cloud services and technologies, including AWS CloudTrail, Kubernetes, Linux, and Apache.

🌟 Key features

• Log management and analytics
• Infrastructure monitoring
• Application observability
• Integrated cloud SIEM

➕ Pros

• Sumo Logic covers logs, metrics, and traces with integrated support for OpenTelemetry
• Provides extensive monitoring for AWS, Azure, GCP, and Kubernetes
• Includes advanced features like anomaly detection, predictive metrics, and automated log-level detection
• Features entity normalization, risk assessment, and automated remediation
• Allows creation of custom dashboards, automated alerts, and tailored visualizations

➖ Cons

Initial configuration can be complex for new users Logs can sometimes be difficult to interpret due to their format

💲 Pricing

Sumo Logic makes it easy to get started with a free plan that offers basic log, metric, and trace capacity, along with a 7-day retention period—perfect if you want to try it out. For growing businesses, the essentials plan steps things up with unlimited log ingestion, enhanced metrics, and standard support, giving you the tools you need to scale confidently. If you need top-tier features, the enterprise suite delivers unlimited capacity, custom data retention, and round-the-clock 24/7 support, making it the go-to choice for large organizations focused on security and compliance.

10. Elastic Cloud

Finish off our list Elastic Cloud, OpenTelemetry backend that combines real-time analysis, powerful search capabilities, and integrated security. It was developed by Elastic, the creators of Elasticsearch, and supports the OpenTelemetry standard, offering SDKs for telemetry data ingestion while maintaining flexibility for custom configurations and avoiding vendor lock-in.

Elastic’s real-time analysis, powered by Elasticsearch, allows interactive visualizations and telemetry data monitoring. This enables you to investigate, analyze, and visualize OpenTelemetry traces, logs, and metrics from a single platform.

Elastic also integrates security best practices into its cloud offering, with features like document- and field-level security to protect sensitive telemetry data. In addition, cross-cluster search and autoscaling capabilities allow you to scale your OpenTelemetry infrastructure effortlessly across regions, providing continuous availability and performance.

Elastic also offers enterprise features like cross-cluster replication, auto-scaling, and real-time monitoring, which are ideal for large-scale OpenTelemetry backends with complex operational needs.

🌟 Key features

• Log management
• Metrics monitoring
• Distributed tracing
• Cross-cluster search
• Service maps
• Event management

➕ Pros

• Unified platform for search, observability, and security
• Deployable across multiple cloud providers, including AWS, Google Cloud, and Microsoft Azure
• Advanced security features, such as document- and field-level access controls, ensure compliance and data protection
• Supports innovative features like large language models and generative AI

➖ Cons

• Pricing can be higher compared to self-managed Elasticsearch deployments
• Resource-intensive, requiring significant compute and storage capacity

💲 Pricing

Elastic Cloud offers several pricing plans to suit different needs. At $95 per month, the standard plan includes core Elastic Stack tools and basic security. The gold plan, priced at $109, adds advanced alerting and reporting. The platinum plan, at $125, includes advanced security and machine learning features. For larger organizations, the enterprise plan at $175 per month offers everything in the platinum plan plus additional enterprise-grade features. Each plan scales to support your growing needs.

Final thoughts

Selecting the proper OpenTelemetry backend is essential for storing and analyzing your logs, metrics, and traces. This article reviewed several backend tools, highlighting their features, pros and cons, and pricing options. With this information, you should better understand which tool best fits your needs. Consider exploring free plans or trial versions to test the most promising solutions and determine which aligns best with your observability requirements.

Article by

Stanley Ulili

Stanley is a freelance web developer and researcher from Malawi. He loves learning new things and writing about them to understand and solidify concepts. He hopes that by sharing his experience, others can learn something from them too!

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