Datadog is a prominent observability platform, offering a vast range of monitoring and performance tracking features. But despite its capabilities, users are still frustrated with its high and unpredictable pricing, which makes full use of features like log storage and querying difficult.
Beyond pricing, others report challenges with enterprise integrations, particularly in setting up TLS and security hardening. These concerns highlight the need for alternatives that provide better pricing transparency, smoother integrations, and greater ease of use.
In this article, we’ll break down the top Datadog alternatives, compare their features, and help you find the right monitoring tool for your business. Let’s dive in!
Why Consider Datadog Alternatives?
While Datadog is a great monitoring tool, it’s not always perfect for your use case. Here are some key reasons why you might look for an alternative:
- Complexity: Multiple features and integrations can become overwhelming. Datadog is not suitable for users who want a simple system because it provides a complex interface with a learning curve.
- Specific Needs: Some industries and businesses need specialized monitoring; whether it’s deeper security insights, compliance tracking, or custom dashboards tailored to unique workflows.
- Flexibility: If you need a highly customizable solution or prefer an open-source approach, Datadog’s all-in-one model might feel limiting. Some alternatives offer more control over how and what you monitor.
- Vendor Lock-In & High Switching Costs – Once committed to Datadog, users report feeling “trapped” in a closed platform, making it difficult to switch or extend functionality compared to open-source solutions.
- High Cost of Data Ingestion: Without proper management, the expenses associated with data ingestion can escalate, making Datadog a potentially costly tool for extensive data monitoring needs.
“Compared to other observability solutions, Middleware offered similar or even superior capabilities at a much lower cost, eliminating the need for expensive tiered pricing or additional charges for advanced features. This made Middleware a more accessible and scalable solution for a business like ours. In fact, we were able to reduce our costs by 75%.”
Prajwal Somashekara, MindOrigin
Given these challenges, several Datadog competitors provide cost-effective, flexible, and specialized monitoring solutions.
Top Datadog Alternatives
Datadog is a popular observability tool, but its pricing complexity and high data ingestion costs push users to seek Datadog alternatives. Whether you need better cost efficiency, more flexible deployment, or deeper insights, here are the top Datadog competitors worth considering in 2025.
1. Middleware
Middleware is an alternative to Datadog, a cost-effective, full-stack observability platform designed for small to medium businesses and DevOps teams. It consolidates logs, metrics, traces, and events into a single real-time timeline, providing complete visibility across cloud and on-prem environments.
Middleware’s data control capabilities allow businesses to manage ingestion costs efficiently, making it a powerful alternative that simplifies observability, reduces overhead, and improves operational efficiency.
With over 200 integrations, Middleware supports AWS, Azure, GCP, Kubernetes, and serverless environments. Its AI-powered search and predictive analytics reduce MTTR, optimize resources, and prevent downtime by identifying anomalies in real-time.
- Consolidates metrics, logs, traces, and events into a single, real-time timeline for end-to-end visibility.
- A lightweight agent that enables quick installation and monitoring of your entire tech stack in minutes.
- Build tailored dashboards and set proactive alerts for critical application and infrastructure issues.
- Provides real-time insights into application performance, latency, errors, and user journeys.
- Helps DevOps teams quickly locate relevant information without manual filtering.
- AI-powered search allows users to query system logs, performance data, and alerts using natural language.
- Correlate data from AWS CloudWatch, Azure Monitor, and on-prem systems in a single view.
Pricing:
- Free Forever: $0 for Full access to all features with monthly limits (100GB data, 1k RUM sessions, 20k synthetic checks, 14-day retention).
- Pay As You Go: $0.3/GB for metrics, logs, and traces, Includes free tier usage, ingestion control, 30-day retention, and dedicated Slack support.
- Enterprise: Custom pricing for volume discounts, premium support, SSO, and advanced security features.
Key differences compared to Datadog:
- Middleware is 3x to 5x more cost-effective than Datadog, with transparent pricing, no hidden fees, and no extra charges for OpenTelemetry metrics or custom metrics.
- Middleware supports on-premise deployment, saving egress costs and ensuring better data security, while Datadog is limited to cloud-only deployment.
- Middleware allows customizable ingestion pipelines, enabling users to monitor only essential data and save costs, whereas Datadog lacks this level of control.
- Middleware offers a wide range of integrations and monitoring capabilities across applications, infrastructure, and logs, making it a strong choice for enterprises with complex environments.
2. New Relic
New Relic is a unified observability platform and a Datadog competitor, providing access to a secure telemetry cloud for all metrics, events, logs, and traces.
Best suited for: Application performance monitoring and enterprise business.
- Offers 700+ integrations, including AI insights and reporting.
- Use error tracking and alerts to identify problems, visualize dependencies, and instantly monitor golden metrics.
- Provides full-stack analysis that covers infrastructure, application performance, and user experience.
- Leverages artificial intelligence and predictive analysis to identify potential issues before they occur.
Pricing:
- Free tier: 100GB/month of data and unlimited basic users.
- Standard: For growing teams with up to 5 full platform users.
- Pro: No user limits and faster customer support.
- Enterprise: All the advanced features plus top-tier security compliance.
Key Differences: New Relic vs. Datadog
- The initial setup of Datadog can be complex with several configuration options, whereas New Relic provides an easier onboarding process with simple setup.
- Datadog provides more detailed controls, while New Relic focuses on easier visualization and simplicity
- New Relic has automatic log collection, while Datadog requires manual configuration but offers advanced filtering.
- Unlike Datadog, which does not offer a free option, New Relic offers a free tier with 100GB/month.
3. Dynatrace
Dynatrace is a Datadog alternative that provides AI-driven automation and observability, offering comprehensive visibility across complex IT environments.
Best suited for: Complex enterprise environments or teams needing AI-powered analytics
- Combines generative, causal, and predictive AI to automate processes, anticipate problems before they arise, and provide accurate root-cause analysis for quicker resolution.
- As Datadog competitors, it automatically maps application and infrastructure dependencies in real-time.
- Out-of-the-box support for AIOps, DevSecOps, cloud migration, and full-stack observability, tailored to large-scale, dynamic environments.
- Enterprise-grade security features make it a powerful alternative to Datadog, especially for organizations prioritizing compliance and data protection.
Pricing:
- Full-Stack Monitoring: $0.08 per hour for 8 GiB host
- Infrastructure Monitoring: $0.04 per hour for any size host.
- Kubernetes Platform Monitoring: $0.002 per hour for any size pod.
- Application Security: $0.018 per hour for 8 GiB host.
- Real User Monitoring: $0.00225 per session.
- Synthetic Monitoring: $0.001 per synthetic request.
- Log Management & Analytics:
- Ingest & Process: $0.20 per GiB.
- Retain with Included Queries: $0.02 per GiB-day (10 to 35-day retention).
Key Differences Compared to Datadog
- Dynatrace provides a unified, real-time topology model that interconnects all observability, security, and business data, while Datadog relies on siloed data stores and manual tagging for dependency mapping.
- For those seeking Datadog competitors, Dynatrace’s AI delivers precise root-cause analysis and intelligent automation by analyzing full-stack data, whereas Datadog’s Watchdog requires manual monitoring setup and lacks comprehensive dependency mapping.
4. Splunk Observability
Splunk Observability, an alternative to Datadog, offers unified visibility across metrics, traces, and logs to help teams troubleshoot faster, ensure reliability, and optimize costs.
- Combines logs, traces, and metrics to give engineering and IT teams full digital insight.
- AI-powered insights and shared workflows help reduce mean time to resolution (MTTR) across complex environments.
- Flexible data ingestion with pay-as-you-go model, optimizing operational costs.
- Integrates with the Splunk Cloud Platform, enabling contextual log analysis alongside observability data.
Pricing
Splunk offers a pay-as-you-go model for all its pricing plans (Workload Pricing, Ingest Pricing, Entity Pricing, Activity-Based Pricing)
Key Differences Compared to Datadog
- Splunk offers flexible, pay-as-you-go pricing models, while Datadog’s decentralized pricing and aggressive fee schedules often lead to unpredictable costs and expensive overages.
- For businesses evaluating Datadog competitors, Splunk provides complete visibility into third-party apps and uses a robust OpenTelemetry implementation, whereas Datadog suffers from blind spots, incomplete trace data, and an over-dependence on manual tagging for search.
- Splunk’s native OpenTelemetry Collector ensures better data portability, lower vendor switching costs, and seamless troubleshooting, while Datadog’s implementation lacks support for span events, live profiling, and standardized data naming.
- Splunk enables better cardinality management and centralized control over data, while Datadog’s minimal centralized control and poor cardinality management make it harder to manage and predict costs effectively.
5. Prometheus and Grafana
Prometheus and Grafana are popular Datadog open-source alternative monitoring solutions that offer powerful and flexible observability for infrastructure and applications. Prometheus excels in metrics collection and alerting, while Grafana provides rich visualization and dashboarding capabilities.
- Both tools are open-source Datadog alternatives, making them ideal for organizations looking to avoid vendor lock-in and high subscription costs.
- Grafana allows teams to create dynamic, interactive dashboards tailored to their specific monitoring needs.
- Prometheus collects and stores time-series data, making it suitable for monitoring large-scale systems.
- Prometheus offers a built-in alert manager that enables proactive monitoring and automated issue detection.
Pricing
- Free Plan: Free forever with capped usage limits.
- Pro Plan ($19/month, Pay-as-You-Go): Includes 10k metrics, 50GB logs/traces, 50k frontend sessions, and usage-based pricing for additional resources.
- Advanced Plan ($299/month): Doubled resource limits, enterprise plugins, 24/7 support, and extended data retention.
Key differences compared to Datadog:
- Grafana is an open-source and Datadog free alternative, with paid plans starting at $19/month, while Datadog’s proprietary SaaS model starts at $23 per host/month, making it costlier for scaling.
- For those looking for a flexible Datadog competitors, Grafana allows extensive customization and integrates with various open-source monitoring tools like Prometheus, while Datadog provides an all-in-one solution with built-in dashboards but less flexibility.
- Datadog offers a fully managed SaaS experience with pre-configured dashboards, whereas Grafana requires manual setup and configuration for data sources making it a powerful alternative to Datadog for businesses wanting full control.
- Grafana can be self-hosted, giving full control over data privacy, while Datadog is a third-party cloud service where data is processed externally.
Comparison Conducted Based on These Key Features
There are various Datadog alternatives and competing monitoring tools available, each with special features. Choosing the best Datadog competitors depends on your monitoring requirements, grows with your company, is user-friendly, integrates easily, and fits within your budget is essential to selecting the best Datadog alternatives.
Here is a list of things to keep in mind while comparing Datadog or trying different platforms:
1. Monitoring Capabilities
Not all tools monitor the same aspects, some focus on infrastructure, others on application performance (APM) or real user monitoring (RUM). When evaluating Datadog alternatives, it’s crucial to define what you need:
- Full-stack vs. specific components: Do you need full visibility or just server health, cloud resources, or application speed?
- Log management: Some tools include built-in logging, while others rely on external solutions, which can be more cost-effective.
- Proactive vs. reactive monitoring: Synthetic monitoring predicts issues before they affect users, while reactive monitoring detects problems after they occur.
2. Scalability
Your monitoring tool must grow with your business to avoid performance bottlenecks or rising costs. Key considerations:
- Handling increased workloads: Some tools work well for small teams but struggle at an enterprise level.
- Hybrid and multi-cloud support: Ensure visibility across on-premise and cloud platforms like AWS, Azure, and GCP.
- Cost predictability: Some solutions become expensive as data volume increases. Looking for a scalable pricing model.
3. Ease of Use
A monitoring tool should be user-friendly, reducing setup time and complexity.
- Quick deployment: The best tools auto-discover infrastructure and services instead of requiring manual setup.
- Intuitive dashboards: Clear, easy-to-read dashboards save time and improve efficiency.
- AI-powered insights: Advanced tools use AI to detect anomalies and send smart alerts, making monitoring more efficient.
“We use Middleware.io for monitoring our cloud infrastructure. It is extremely easy to integrate and provides a comprehensive view of your cloud environment with a very affordable price.”
Artem Harutyunyan, Bardeen.ai
4. Integration Options
Your observability tool should work with the tech you already use. A monitoring system that doesn’t play well with others can create data silos making it tougher to fix problems quickly.
- Does it work with your DevOps setup? If your team uses Kubernetes, Terraform, or CI/CD pipelines, try to find a tool that works with these platforms. This helps you keep an eye on deployments, spot problems, and undo changes if needed.
- How well does it bring data together? Many companies use different tools for logs, security checks, and performance tracking. A good observability tool should let you gather data from many places, so you can see how everything’s working without jumping between different tools.
- Does it support OpenTelemetry or other open standards? Getting stuck with one vendor can cause big problems if you want to change tools later. OpenTelemetry support means your data can move and work with different monitoring tools, which cuts down on long-term risks.
5. Pricing & Long-Term Cost Considerations
Price isn’t the whole story; it’s about getting your money’s worth. Many monitoring tools seem cheap at first but bring unexpected expenses as your system grows.
- How do they charge? Some platforms base their fees on the number of hosts, others on data volume, and some use a mix of factors. If your company relies on data, pricing based on ingestion can get pricey fast. If you have a big infrastructure, paying per host might suit you better.
- Do they ask for more money to keep old data? Some tools charge extra to store logs or metrics past a certain time. If you need to keep data for a long time because of rules or safety concerns, check if the pricing plan allows for this.
- Do you try it for free or pay for what you use? For businesses that see big jumps in traffic at certain times, a flexible pricing plan can save more money than a set subscription. Pay-as-you-go options let you use more during busy times and less when it’s quiet.
Final Thoughts: Selecting the Appropriate Alternative
No one monitoring tool is ideal for everyone. The best one for you will depend on what you are monitoring, how much data you process, how sophisticated your infrastructure is, and how much money you have to spend.
Comparing other options isn’t merely a matter of changing tools; it’s about discovering the optimal solution for your business. Perhaps you want something less expensive, a more scalable platform, or a tool that integrates more easily with your workflow. Spending time comparing alternatives guarantees you receive a monitoring solution that serves your purposes.
Once you’ve identified a few strong contenders, dive deeper. Try out free trials, read user reviews, and test how well each tool integrates with your existing setup. Hands-on experience is the best way to find the right match!
FAQs
What are the key differences between Datadog and its competitors?
Datadog is unique in its end-to-end, single-platform monitoring, combining metrics, logs, and traces with AI-driven alerting. Alternatives such as New Relic and Middleware are more flexible, configurable, and open-source.
Is there a free alternative to Datadog?
Yes, both Grafana and Zabbix have free, open-source offerings. Zabbix may be self-hosted and Grafana is highly flexible due to integrations, but they can take more technical know-how to implement and manage.
Can I use multiple monitoring tools simultaneously?
Yes, it is possible and in some cases advisable to run multiple monitoring tools for various reasons. For instance, running Grafana to visualize data from various sources and Datadog for end-to-end monitoring can provide more complete insights
