You’re here because your Datadog bill is out of control, you’re tired of navigating a UI with a million knobs, or you’re getting that sinking feeling of being locked into a proprietary ecosystem. You’re not alone.
Datadog is the 800-pound gorilla of observability, and for a long time, it was the default choice. But the cloud-native world has changed, and the “one-size-fits-all” monolith isn’t always the right fit anymore.
The good news is, there are now a ton of excellent Datadog alternatives that might be a better match for your team’s workflow, architecture, and most importantly your budget.
In this article, we'll look at the top contenders, what they get right, and where they fall short, so you can make a decision that won’t give you buyer’s remorse next quarter.
1. Dash0
Dash0 is a modern observability platform built from the ground up on open standards. It’s designed for cloud-native teams who live and breathe OpenTelemetry and Prometheus and don’t want to be handcuffed to a vendor’s proprietary tech. The whole philosophy is about giving you control over your telemetry data and costs without sacrificing capability. It unifies logs, metrics, and traces into one clean interface with a single, open query language.
What’s good
- Zero lock-in by design. Dash0 is OpenTelemetry-native, meaning it works with OTLP out of the box. It also fully supports PromQL for queries and Perses for dashboards, so you can bring your existing configurations with you and take them if you leave. Your data, your tools.
- Transparent and predictable pricing. The pricing model is dead simple: you pay per million signals (logs, spans, metric data points). There are no confusing tiers based on hosts, no per-user fees that punish you for growing your team, and no surprise charges for running too many queries. You can finally forecast your observability spend without a Ph.D. in finance.
- One query language for everything. Instead of forcing you to learn one language for logs, another for metrics, and yet another for traces, Dash0 uses PromQL for all three. This massively reduces the learning curve and simplifies workflows. If you know Prometheus, you already know how to use Dash0.
The catch
- Focused on the OTel/Prometheus ecosystem. This is a strength if you’re bought into open standards, but if your entire stack is built around a different proprietary agent, you’ll need to instrument with OpenTelemetry to get the full value. The platform is built for the future, not to support every legacy agent from the past.
The verdict
Dash0 is the top choice for any team that values open standards, cost control, and a streamlined workflow. If you’re using (or switching to) OpenTelemetry, and want a platform that respects your freedom as a developer, this is it.
It’s one of the best Datadog alternatives that doesn’t compromise on core observability principles. It gives you the essentials and more in a clean and intuitive package without the vendor lock-in and bill shock.
Ready for Observability Without the Lock-In? Give Dash0 a spin with a 14-day free trial.
2. New Relic
New Relic is one of the original APM players and a direct competitor to Datadog. They’ve been around for a long time and have a mature platform that covers everything from infrastructure monitoring and APM to browser and mobile monitoring. They recently revamped their pricing and platform to be more unified, positioning themselves as a more accessible alternative.
What’s good
- Generous free tier. New Relic’s free tier is one of the most generous in the industry, offering 100GB of data ingest per month and one full user for free. This makes it a great option for small projects or for teams wanting to try it out thoroughly.
- Mature APM capabilities. They have deep experience in application performance monitoring. Their agents provide detailed transaction traces, dependency mapping, and code-level diagnostics that are well-regarded.
- Simplified pricing model. They moved to a usage-based model (per GB ingested) and per-user pricing, which is simpler to understand than their old, complex product-based tiers.
The catch
- The cost can still get complicated. While simpler, the pricing model combining data ingest and per-user fees can still lead to unpredictable bills. The “full platform” users can get expensive, and you need to watch your data ingest closely, just like with Datadog.
- Proprietary roots show. While they have embraced OpenTelemetry, the platform was built around their own proprietary agents. The experience can sometimes feel less seamless for OTel-native data compared to their own agents, and you might not get the full value of their platform without using their instrumentation.
- Can feel like a monolith. Like Datadog, it’s a huge platform with a ton of features. This can be overwhelming for teams that just need the basics, and the UI can feel cluttered if you’re not using every single module.
The verdict
New Relic is a solid Datadog alternative, especially if you’re looking for a mature APM solution with a generous free tier to get started. It’s a good choice for enterprises that want an all-in-one platform. However, be mindful of the per-user costs and the potential for vendor lock-in if you lean too heavily on their proprietary agents and features.
3. Dynatrace
Dynatrace is another enterprise-focused observability giant, often competing with Datadog for large corporate accounts. Its key differentiator is its AI engine, “Davis,” which is designed to automate root cause analysis and anomaly detection, requiring less manual intervention.
What’s good
- Powerful AI and automation. Dynatrace’s AI-powered root cause analysis is its main selling point. It automatically discovers your environment, maps dependencies, and pinpoints the source of problems, which can significantly reduce manual troubleshooting time.
- Strong APM and tracing. Their proprietary “PurePath” technology offers deep, code-level visibility into transactions. It’s designed for complex, enterprise-grade applications.
- Relatively straightforward setup. For what it does, the initial setup with their OneAgent is quite automated. It handles discovery and instrumentation with minimal configuration.
The catch
- It’s expensive and the pricing is complex. Dynatrace is priced for the enterprise, and its consumption-based pricing model has many different units (Host Units, GiB for logs, etc.) that can be difficult to predict and manage. This isn’t a cheaper Datadog alternative.
- Heavy on proprietary tech. The platform is heavily reliant on its OneAgent and PurePath technology. While they support OpenTelemetry data ingestion, the core value and automation are tied to their proprietary ecosystem, creating significant vendor lock-in.
- Less hands-on control. The high degree of automation can be a double-edged sword. For SREs who want to dig into the raw data and have fine-grained control over their queries and dashboards, Dynatrace’s “black box” approach can feel restrictive.
The verdict
Dynatrace is for large enterprises that want a highly automated, AI-driven observability platform and are willing to pay a premium for it. If your organization wants to minimize the hands-on SRE work of troubleshooting and prefers a tool that provides “the answer,” it’s a strong contender. But for teams that want control, flexibility, and to avoid proprietary lock-in, it’s probably not the right fit.
4. Splunk Observability Cloud
Splunk, the long-reigning king of log management, has expanded into a full observability platform by acquiring companies like SignalFx (for metrics and APM) and Plumbr. Their Observability Cloud aims to provide a unified solution for infrastructure, APM, and RUM, leveraging their deep expertise in data analysis.
What’s good
- Best-in-class log analysis. Splunk’s Search Processing Language (SPL) is incredibly flexible for searching and analyzing logs. If your primary pain point is complex log investigation, Splunk is still a top-tier solution.
- Strong enterprise integrations. Splunk has been in the enterprise game for a long time and has a massive ecosystem of apps and integrations for various enterprise systems.
- Real-time streaming architecture. The platform is built on a streaming architecture that allows for real-time alerting on metrics and traces, which is great for incident response.
The catch
- Extremely expensive. Splunk is notorious for its high cost. Pricing is complex and can be based on data volume, compute capacity, or hosts, making it one of the most expensive options on the market.
- A stitched-together experience. The Observability Cloud is a result of acquisitions, and sometimes it shows. The workflow between logs (Splunk core), metrics (SignalFx), and traces can feel less integrated than platforms built from the ground up as a unified solution.
- Learning curve. SPL is a language unto itself. While it’s a great tool, it requires a significant investment to learn. The platform as a whole is complex and not for the faint of heart.
The verdict
Splunk is a heavyweight contender for large enterprises already invested in the Splunk ecosystem for logging or SIEM. If money is no object and your primary need is deep log analytics with added observability features, it’s worth a look. However, for most cloud-native teams, the cost and complexity make it a non-starter.
5. Grafana Stack
Grafana started as the de-facto open-source tool for visualizing metrics and has evolved into a full observability stack with Loki for logs, Tempo for traces, and Mimir for metrics. You can run it yourself or use Grafana Cloud, their managed service. It’s the quintessential open source Datadog alternative.
What’s good
- Open source and flexible. The biggest advantage of Grafana is its open-source nature. You have complete control and can avoid vendor lock-in. The community is huge, with a vast library of dashboards and plugins.
- Excellent visualization. Grafana’s dashboarding capabilities are top-notch. It’s incredibly flexible for creating beautiful, data-rich visualizations from almost any data source.
- Cost-effective, especially if self-hosted. If you have the engineering resources to manage it yourself, the Grafana stack can be a very cheap option. Grafana Cloud is also competitively priced compared to Datadog.
The catch
- High operational burden (if self-hosted). Running and scaling Loki, Tempo, and Mimir in production is a full-time job. You’re responsible for storage, availability, and performance, which can be a massive undertaking.
- A less unified experience. While improving, the three pillars (logs, metrics, traces) can still feel like separate tools. Correlating data between them isn’t always as smooth as in a platform designed as a single unit from the start. You also have to deal with different query languages (LogQL for Loki, TraceQL for Tempo, PromQL for Mimir).
- Grafana Cloud can get pricey with scale. The managed offering is convenient, but the usage-based pricing can add up quickly, especially with high-cardinality metrics or large log volumes.
The verdict
The Grafana Stack is for teams that are all-in on open source and have the engineering expertise to manage it, or for those who want a managed, highly customizable visualization platform with Grafana Cloud.
It’s a fantastic Datadog alternatives free option if you self-host. However, be prepared for the operational overhead or the potentially high costs of the managed service at scale.
6. Signoz
Signoz is a true open-source, OpenTelemetry-native Datadog alternative. It aims to provide a unified experience for metrics, traces, and logs in a single application. It’s built to be a direct replacement for proprietary tools, offering a similar all-in-one feel but with the transparency and flexibility of open source.
What’s good
- OpenTelemetry-native. Signoz was built specifically for OpenTelemetry. It uses OTel for instrumentation and OTLP for data ingestion, making it a natural fit for modern, cloud-native applications.
- Unified single application. Unlike the Grafana stack, Signoz is a single binary. This simplifies deployment and management, providing a more cohesive experience for correlating signals.
- ClickHouse for storage. It uses ClickHouse as its backend database, which is designed for fast analytical queries on large datasets, giving it impressive query performance.
The catch
- It’s still maturing. Signoz is a relatively new project compared to the giants. While it’s developing rapidly, it may lack some of the more advanced features, integrations, and polish of a tool like Datadog.
- Self-hosting complexity. Like any self-hosted solution, you are responsible for the care and feeding of the platform. While simpler than the full Grafana stack, you still need to manage the infrastructure, scaling, and updates.
- Smaller community. The community and ecosystem around Signoz are growing but are still much smaller than Grafana’s or Prometheus’s.
The verdict
Signoz is an exciting datadog alternatives open source project for teams that want a unified, OTel-native observability platform without paying for a SaaS vendor. It’s ideal for startups and engineering teams who are comfortable running their own infrastructure and want to bet on a promising, modern open-source tool.
7. Better Stack
Better Stack started with a focus on beautiful and fast log management and has since expanded to include uptime monitoring, incident management, and status pages. They market themselves as a simpler, more affordable, and more aesthetically pleasing alternative to complex platforms.
What’s good
- Excellent UI/UX. Better Stack’s interface is clean, fast, and intuitive. It’s a pleasure to use, especially their log search, which feels like a modern command-line tool in the browser.
- Affordable and predictable pricing. Their pricing is based on data volume with generous retention periods, making it a cheaper alternative to Datadog. It’s much easier to predict your costs.
- Integrated incident management. Having uptime, logging, and incident management in one place creates a tight feedback loop for on-call engineers.
The catch
- Not a full-stack observability platform (yet). While they’ve added metrics, their core strength remains in logging and incident management. The APM, metrics, and tracing capabilities are either not as mature or non-existent.
- Less focus on deep infrastructure monitoring. If you need detailed Kubernetes monitoring, host-level metrics, and complex infrastructure dashboards, you might find Better Stack’s capabilities limiting compared to the competition.
The verdict
Better Stack is a good choice for teams whose primary concern is logging and who want a simple, beautiful, and affordable platform for log analysis, uptime monitoring, and on-call management.
If you’re looking for a Loggly or Papertrail replacement with modern sensibilities, it’s a top contender. However, if you need deep APM, tracing, and infrastructure monitoring, you may need to supplement it with another tool.
8. Chronosphere
Chronosphere was founded by the creators of M3, Uber’s open-source metrics engine. The platform is built to solve the problem of observability data growth at a massive scale. Its core value proposition is a control plane that helps you shape and triage your telemetry data before you pay to store it.
What’s good
- Controls data growth. Chronosphere’s platform is specifically designed to handle high-cardinality metrics without falling over. Its processing pipeline allows you to aggregate, drop, or transform metrics based on rules, giving you fine-grained control over costs.
- Open-source compatible. It’s compatible with Prometheus and other open-source tools. You can use PromQL and Grafana dashboards, which reduces the learning curve and avoids lock-in for your visualizations.
- Built for massive scale. This tool is engineered for the kind of scale that most companies can only dream of. If you’re running a global infrastructure with millions of time series, Chronosphere is built for you.
The catch
- Very expensive for most. Chronosphere is a premium product targeted at a specific problem. While it can save money for companies at extreme scale by reducing data volume, its entry price is very high, putting it out of reach for most startups and mid-sized companies.
- Focused primarily on metrics. While they have added support for traces, their DNA is in metrics. The experience for logs and other signals is not as developed as their metrics pipeline.
- Complex setup. The control plane that gives you power over your data is also complex to configure. Getting the most out of it requires a significant upfront investment in learning and configuration.
The verdict
Chronosphere is a niche tool for large, mature tech companies struggling with an explosion of metrics data at a scale where Datadog becomes prohibitively expensive. It’s less a general-purpose Datadog alternative and more a specialized, high-end solution for a very specific, high-scale pain point.
9. Honeycomb
Honeycomb pioneered the concept of “observability” as we know it today, with a focus on distributed tracing and high-cardinality events. Their philosophy is that wide, arbitrary-width structured events are the future, replacing the traditional three pillars.
What’s good
- Best-in-class distributed tracing. Their “BubbleUp” feature, which helps you spot patterns in high-cardinality data, is a unique and incredibly useful way to debug.
- Built for high cardinality. The entire platform is designed to let you slice and dice your data by any dimension without fear. You can ask questions about specific users, tenants, or feature flags without the tool falling over.
- Great developer experience. Honeycomb is built by engineers for engineers. Their documentation is excellent, and their focus on helping developers solve real-world problems is evident throughout the product.
The catch
- Event-based model requires a mental shift. Thinking in “events” instead of separate metrics, logs, and traces requires a change in mindset and instrumentation strategy.
- Metrics and logging are secondary. While Honeycomb can ingest and display metrics and logs, they are treated as types of events. The experience is not the same as a dedicated metrics or logging solution, and you might miss some traditional features.
The verdict
Honeycomb is for engineering teams that are all-in on modern observability practices and see distributed tracing as the cornerstone of their debugging workflow. It’s not a drop-in Datadog replacement, but a different way of thinking about observability.
10. Elastic Observability
Built on the popular Elasticsearch, Logstash, and Kibana (ELK) stack, Elastic Observability is a natural extension for teams already using Elastic for log management. It integrates APM (tracing), metrics, and logging into Kibana, providing a unified search and analytics experience.
What’s good
- Unified search with Kibana. If you’re already an Elasticsearch power user, having all your telemetry in one place, searchable with the same tools, is a huge win.
- Strong logging capabilities. At its core, Elastic is a search engine. It excels at searching, filtering, and aggregating massive volumes of log data.
- Flexible deployment. You can use their managed Elastic Cloud or host the entire stack yourself for maximum control, making it a potential free datadog alternative option if you have the hardware and expertise.
The catch
- Complexity and resource-intensive. The ELK stack is notoriously complex to manage and scale. It requires significant engineering resources to maintain performance and reliability. Even on Elastic Cloud, you need to be an expert in managing indices and clusters to control costs.
- APM is less mature. While their APM has improved, it’s still widely considered to be less mature and feature-rich than competitors like Datadog or New Relic. The experience can sometimes feel bolted on rather than natively integrated.
- Proprietary agent focus. Like others, they encourage the use of their Elastic Agent. While they have OpenTelemetry support, you often get a better experience and more features by using their proprietary components, which leads down the path to lock-in.
The verdict
Elastic Observability is the logical choice for teams that are already heavily invested in the Elasticsearch ecosystem. If your organization lives and breathes Kibana, it makes sense to consolidate your observability data there. However, for teams starting fresh, the complexity, operational overhead, and less mature APM make other alternatives on this list more appealing.
11. ServiceNow Cloud Observability (Lightstep)
Lightstep was an early pioneer in distributed tracing, founded by one of the co-creators of Google’s Dapper. It was acquired by ServiceNow and is now the core of their Cloud Observability offering. Lightstep’s key innovation was its ability to perform root cause analysis across massive trace datasets by separating the metric-like data from the trace data.
What’s good
- Powerful trace analysis. Lightstep excels at analyzing large volumes of trace data to quickly identify latency and error contributors. Its “Change Intelligence” feature automatically correlates performance deviations with deployments.
- Built on OpenTelemetry. Lightstep was an early and enthusiastic adopter of OpenTelemetry and has contributed significantly to the project. The platform is designed to work seamlessly with OTel data.
- Scalable architecture. The underlying satellite architecture is designed to handle massive amounts of telemetry data at the edge, reducing the amount of data that needs to be sent to the central platform for analysis.
The catch
- Uncertainty after acquisition. Being part of a massive enterprise company like ServiceNow can be a mixed bag. The pace of innovation can slow down, and the product roadmap may be driven by large enterprise needs rather than the developer community.
- Pricing can be opaque. The pricing is now tied into the broader ServiceNow ecosystem. It’s not as simple and transparent as it once was, and it’s generally targeted at the enterprise market.
- Less of a unified platform. While it has metrics and logging capabilities, its core strength and focus have always been on tracing. The experience for other signals may not be as rich as all-in-one platforms.
The verdict
Lightstep is a strong contender for organizations that need to analyze distributed traces at a very large scale and are brought into the OpenTelemetry ecosystem. It’s particularly well-suited for performance-sensitive applications where understanding trace data is paramount.
However, the ServiceNow acquisition and enterprise focus may make it less appealing for smaller, more agile teams who prefer transparent pricing and a simpler, developer-focused tool.
Final thoughts
The days of Datadog being the only serious player in the game are over, but the right alternative for you depends entirely on your team’s priorities.
If you’re an enterprise that wants an all-in-one box with a huge feature set, New Relic or Dynatrace are still viable. If you’re a die-hard open-source team with engineering capacity to spare, the Grafana stack offers ultimate flexibility. And if your main problem is debugging complex microservices, Honeycomb’s trace-first approach is second to none.
But for most modern, cloud-native teams, the sweet spot lies with a platform that embraces open standards, offers predictable pricing, and provides a clean, unified workflow without the bloat.
The goal is to spend less time fighting your tools and managing your observability bill, and more time building and shipping reliable software. That’s why a solution like Dash0, built from the ground up on OpenTelemetry and PromQL, represents the future.
