10 melhores alternativas ao Datadog para monitorização na nuvem em 2026

By
Paulo Gardini Miguel

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Analisei e avaliei as alternativas ao Datadog mais populares e selecionei as minhas principais escolhas para melhorar as capacidades de monitorização e reduzir os custos.

Se utiliza o Datadog para monitorizar a nuvem, poderá ter encontrado desafios, como custos elevados ou funcionalidades complexas que não se adequam às necessidades da sua equipa. Não é o único. Muitos especialistas em tecnologia procuram alternativas ao Datadog que correspondam melhor aos seus requisitos específicos.

Com base na minha experiência, encontrar a ferramenta certa pode aumentar significativamente a eficiência da sua equipa. Foi por isso que testei e analisei de forma independente várias alternativas ao Datadog. O meu objetivo é fornecer-lhe um guia imparcial e bem fundamentado que o ajude a tomar uma decisão informada.

Neste artigo, partilharei as minhas principais escolhas de alternativas ao Datadog, com foco nas funcionalidades e vantagens únicas que poderão adequar-se melhor à sua equipa. Vamos explorar as opções que poderão responder melhor às necessidades da sua empresa.

O que é o Datadog?

O Datadog é uma plataforma de monitorização na nuvem que ajuda a acompanhar as suas aplicações, infraestrutura e registos em tempo real. Os profissionais de TI, os programadores e as equipas de operações utilizam geralmente o Datadog para monitorizar o desempenho e resolver problemas rapidamente. Funcionalidades como a monitorização em tempo real, a gestão de registos e os painéis personalizáveis ajudam a identificar estrangulamentos de desempenho e a manter o bom funcionamento dos sistemas. De um modo geral, o Datadog oferece uma forma simples de manter os seus sistemas a funcionar sem problemas.

Tabela de comparação das alternativas ao Datadog

Esta tabela de comparação resume os detalhes dos preços das minhas principais escolhas de alternativas ao Datadog:

1Best for flexible data retention14-day free trialFrom $0.06/GBWebsite
2Best for AI-driven dependency mapping at scale15-day free trialFrom $7/monthWebsite
3Best for data-source-agnostic visualizationFree plan + free trial availableFrom $19/month + usageWebsite
4Best unified full-stack telemetry ecosystemFree plan availableFrom $10/user/monthWebsite
5Best for enterprise-grade security analytics60-day free trialPricing upon requestWebsite
6Best pull-based metrics engine for KubernetesFree plan availablePricing upon requestWebsite
7Best for real-time app discoveryFree demo availableFrom $21.20/MVS/monthWebsite
8Best for AWS environmentsFree plan + 3-month free trial availablePricing upon requestWebsite
9Best for large-scale log searchFree trial + free demo availableFrom $0.07/GB data ingestedWebsite
10Best for Azure integrationFree demo availablePricing upon requestWebsite

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Análises das melhores alternativas ao Datadog

Apresentamos abaixo os meus resumos detalhados das melhores alternativas ao Datadog que integraram a minha lista restrita. As minhas análises oferecem uma visão detalhada das principais funcionalidades, vantagens e desvantagens, integrações e casos de utilização ideais de cada ferramenta, para o ajudar a encontrar a melhor opção para si.

  1. Best for flexible data retention
    • 14-day free trial
    • From $0.06/GB
    Visit Website
    Customer Rating:4.8/5
    Coralogix screenshot
    Coralogix tracks database queries, latency, errors, and operations in real time.

    Coralogix is a log analytics and monitoring platform designed for DevOps teams and IT professionals. It helps you manage and analyze log data to gain insights and improve system performance.

    Why it's a good Datadog alternative: Coralogix offers flexible data retention options, allowing you to control how long you keep your data. Its real-time analytics provide immediate insights into your logs. With machine learning capabilities, Coralogix helps you identify patterns and anomalies quickly. This can be particularly useful for teams looking to optimize data storage and retrieval.

    Standout Features and Integrations:

    Features include live tailing, which lets you view log data in real-time to catch issues as they happen. The platform's machine learning algorithms improve anomaly detection. You can also use its customizable dashboards to focus on the metrics that matter most to your team.

    Integrations include AWS, Microsoft Azure, Google Cloud Platform, Kubernetes, Docker, GitHub, Slack, Jira, PagerDuty, and more.

    Pros and Cons

    Pros:

    • Machine learning insights, including immediate anomaly detection
    • Real-time log analytics
    • Flexible data retention

    Cons:

    • Tiered configurations can become expensive
    • Complex interface and proprietary query language
    Learn more about Coralogix:
  2. Best for AI-driven dependency mapping at scale
    • 15-day free trial
    • From $7/month
    Visit Website
    Customer Rating:4.5/5
    Dynatrace screenshot
    Dynatrace monitors AWS with EC2 metrics, heatmaps, logs, and problem tracking.

    Dynatrace is an AI-powered monitoring platform used by IT and DevOps teams to gain insights into infrastructure and application performance across the entire stack. It automates monitoring and provides real-time data to optimize your systems.

    Why it's a good Datadog alternative: Dynatrace's AI-driven insights help you automatically detect anomalies and predict issues before they affect users. Its full-stack monitoring covers everything from applications to microservices, providing a unified view. The AI capabilities also reduce manual work by offering automated root cause analysis. This makes it easier for your team to focus on strategic tasks rather than firefighting.

    Standout Features and Integrations:

    Features include real user monitoring, which provides insights into user experiences. The platform's automatic discovery maps out your entire IT environment. You also get access to API monitoring, making your integrations perform well.

    Integrations include AWS, Microsoft Azure, Google Cloud, Kubernetes, ServiceNow, Slack, Jira, VMware, SAP, IBM, and more.

    Pros and Cons

    Pros:

    • Scalable for large enterprises
    • AI-driven root cause analysis
    • Causal topology mapping

    Cons:

    • Higher licensing cost
    • Challenging submenu interface
  3. Best for data-source-agnostic visualization
    • Free plan + free trial available
    • From $19/month + usage
    Visit Website
    Customer Rating:4.6/5
    Grafana screenshot
    Grafana shows real-time site performance with CPU, requests, and load time.

    Grafana is a data visualization and monitoring platform used by IT and DevOps teams to create interactive and shareable dashboards. It helps you monitor and analyze metrics from various data sources.

    Why it's a good Datadog alternative: Grafana excels in visualizing metrics with its wide range of customizable dashboards. You can tailor these dashboards to display the data that's most relevant to your team. The platform's flexible alerting system keeps you informed about critical changes. Its open-source nature means you can adapt it to fit your exact needs.

    Standout Features and Integrations:

    Features include templating, which lets you create reusable and dynamic dashboards. The annotation feature helps you mark important events on graphs for context. You can also use its alerting capabilities to receive notifications based on specific thresholds.

    Integrations include Grafana Labs stack, Prometheus, InfluxDB, Elasticsearch, AWS CloudWatch, Microsoft Azure Monitor, Google Cloud, MySQL, PostgreSQL, Graphite, OpenTSDB, and more.

    Pros and Cons

    Pros:

    • Strong visualization capabilities
    • Efficient data aggregation
    • Advanced multi-source visualization

    Cons:

    • Limited built-in analytics
    • High operational complexity
  4. Best unified full-stack telemetry ecosystem
    • Free plan available
    • From $10/user/month
    Visit Website
    Customer Rating:4.3/5
    New Relic screenshot
    New Relic offers real-time monitoring with alerts and custom dashboards.

    New Relic is an application performance monitoring (APM) tool utilized by developers and IT operations teams to ensure optimal application performance. It provides insights into application behavior and infrastructure health.

    Why it's a good Datadog alternative: With extensive integrations, New Relic allows you to connect to a wide variety of services and platforms. Its real-time APM and alerting features help you stay on top of performance issues. Customizable dashboards give you the flexibility to tailor metrics to your team's needs. This makes it easier to manage complex environments with diverse technologies.

    Standout Features and Integrations:

    Features include synthetic monitoring, which simulates user interactions to catch issues early. Distributed tracing helps you understand the flow of requests in your applications. You can also use advanced analytics to gain deeper insights into your data.

    Integrations include AWS, Microsoft Azure, Google Cloud, Kubernetes, Docker, Slack, PagerDuty, Jenkins, GitHub, Jira, and more.

    Pros and Cons

    Pros:

    • Consolidated entity-centric view
    • Powerful APM and tracing
    • Extensive integration options

    Cons:

    • Some features require advanced setup
    • Complex pricing model
  5. Best for enterprise-grade security analytics
    • 60-day free trial
    • Pricing upon request
    Visit Website
    Customer Rating:4.3/5
    Splunk screenshot
    Splunk shows real-time intrusion alerts, threat levels, and attack maps.

    Splunk is a data analytics platform used by IT and security professionals to monitor and analyze machine-generated data. It helps you gain insights from logs, metrics, and events to improve operational performance and security.

    Why it's a good Datadog alternative: Splunk excels in security analytics, including SIEM, providing advanced threat detection and response capabilities. Its powerful search and visualization tools enable you to quickly identify and mitigate security risks. The platform's ability to handle large data volumes makes it suitable for complex environments. You can also customize dashboards to focus on the security metrics that matter most to your team.

    Standout features and integrations:

    Features include advanced search capabilities that allow you to explore your data in detail. The platform's machine learning tools improve predictive analytics for better decision-making. You can also benefit from real-time monitoring to keep your systems secure.

    Integrations include AWS, Microsoft Azure, Google Cloud Platform, AppDynamics, ServiceNow, Docker, Kubernetes, Salesforce, Cisco, Okta, Palo Alto Networks, and more.

    Pros and Cons

    Pros:

    • Extensive integration marketplace
    • Strong security and SIEM tools
    • Advanced log analytics

    Cons:

    • High total cost of ownership
    • Heavy indexer maintenance
  6. Best pull-based metrics engine for Kubernetes
    • Free plan available
    • Pricing upon request
    Visit Website
    Customer Rating:4.4/5
    Prometheus screenshot
    Prometheus monitors Kubernetes pods, CPU, memory, and filesystem usage.

    Prometheus is an open-source monitoring and alerting toolkit primarily used by developers and IT operations teams. It focuses on capturing time series data to provide insights into system performance and reliability.

    Why it's a good Datadog alternative: Prometheus provides an open-source solution allowing for a high degree of customization and flexibility. Its powerful query language, PromQL, lets you explore and analyze data efficiently. The tool's focus on time series data helps you monitor and alert on key metrics. Plus, its ability to integrate with various systems makes it adaptable to different environments.

    Standout Features and Integrations:

    Features include a flexible data model that supports multi-dimensional data collection. The alert manager allows you to define and manage alerts effectively. You can also use built-in visualization tools to create insightful dashboards.

    Integrations include Kubernetes, Docker, Consul, etcd, Amazon EC2, Google Cloud Platform, Microsoft Azure, DigitalOcean, and Grafana.

    Pros and Cons

    Pros:

    • Efficient time-series data handling
    • Customizable query language
    • Open-source flexibility

    Cons:

    • No native long-term storage
    • Limited built-in visualization
  7. Best for real-time app discovery
    • Free demo available
    • From $21.20/MVS/month
    IBM Instana screenshot
    IBM Instana shows real-time app performance, errors, latency, and insights.

    IBM Instana is an APM tool designed for DevOps and IT operations teams. It provides real-time insights into application performance and infrastructure health.

    Why it's a good Datadog alternative: With real-time AI insights and correlation capabilities, IBM Instana automatically detects issues and provides actionable data to resolve them. Its automatic discovery and mapping of services gives you a complete view of your environment. The tool's AI-driven root cause analysis helps you quickly identify and fix problems. Continuous updates mean your team always has the latest information at their fingertips.

    Standout Features and Integrations:

    Features include continuous integration with DevOps workflows to improve your team's efficiency. The platform offers end-to-end transaction tracing to monitor the user experience. You can also access detailed infrastructure monitoring for deeper insights into system performance.

    Integrations include Kubernetes, Docker, AWS, Microsoft Azure, Google Cloud Platform, IBM Cloud, Red Hat OpenShift, VMware, Jenkins, Grafana, and more.

    Pros and Cons

    Pros:

    • Strong Kubernetes support
    • Automatic dependency mapping
    • Real-time tracing and monitoring

    Cons:

    • Steep initial configuration
    • Opaque per-MVS pricing
    Learn more about IBM Instana:
  8. Best for AWS environments
    • Free plan + 3-month free trial available
    • Pricing upon request
    Amazon CloudWatch screenshot
    Amazon CloudWatch tracks Amazon Bedrock model metrics in real-time dashboards.

    Amazon CloudWatch is a monitoring and management service built for developers, system operators, and IT managers who are using AWS resources. It helps you collect and track metrics, monitor log files, and set alarms.

    Why it's a good Datadog alternative: With its deep integration with AWS, Amazon CloudWatch offers coherent monitoring of all your AWS resources. It provides detailed performance data and operational health insights. The service's ability to set alarms based on metric thresholds helps in proactive management. Additionally, its automatic scaling feature maintains your application's performance levels.

    Standout Features and Integrations:

    Features include detailed monitoring, allowing you to collect and analyze metrics at one-minute intervals. The service also offers log data storage and management, helping you troubleshoot issues quickly. You can set custom dashboards to visualize metrics that matter most to your team.

    Integrations include AWS Lambda, Amazon EC2, Amazon S3, Amazon RDS, Amazon ECS, AWS Elastic Beanstalk, Amazon API Gateway, AWS CloudTrail, AWS Step Functions, AWS IoT, and more.

    Pros and Cons

    Pros:

    • Customizable alarms
    • Detailed performance data
    • Integrated with AWS security

    Cons:

    • Requires AWS expertise
    • Limited cross-cloud visibility
    Learn more about Amazon CloudWatch:
  9. Best for large-scale log search
    • Free trial + free demo available
    • From $0.07/GB data ingested
    Elastic screenshot
    Elastic's analytics include core web vitals, load times, and visitor insights.

    Elastic is a search-powered analytics platform that serves developers and IT teams needing to search, analyze, and visualize data in real time. It supports various functions, including logging, security, and observability.

    Why it's a good Datadog alternative: Elastic excels in search capabilities, making it easier to find and analyze specific data points. Its observability tools provide deep insights into application performance and infrastructure health. The platform's scalability allows you to handle large volumes of data efficiently. With customizable dashboards, your team can focus on the metrics that matter most.

    Standout Features and Integrations:

    Features include powerful search capabilities that let you query large datasets quickly. The platform's machine learning features help you detect anomalies in your data. You can also use its visualization tools to create insightful dashboards that highlight key metrics.

    Integrations include Kubernetes, Docker, AWS, Microsoft Azure, Google Cloud Platform, Apache Kafka, Apache Hadoop, Logstash, Beats, MySQL, and more.

    Pros and Cons

    Pros:

    • Highly flexible data ingestion methods
    • Scalable log and metrics analysis
    • Strong full-text search capabilities

    Cons:

    • Can be resource-intensive
    • Potential for operational lock-in
  10. Best for Azure integration
    • Free demo available
    • Pricing upon request
    Azure Monitor screenshot
    Azure Monitor tracks app usage, reliability, response times, and CPU metrics.

    Azure Monitor is an all-in-one monitoring service designed for IT professionals and developers using Microsoft Azure. It collects, analyzes, and acts on telemetry data from your cloud and on-premises environments.

    Why it's a good Datadog alternative: With native Microsoft Azure integration, Azure Monitor provides smooth monitoring across your Azure resources. It offers built-in analytics for deep insights into your applications. The service's ability to create alerts based on custom metrics notifies you promptly about any pipeline issues. Additionally, its scalability supports large and dynamic environments, making it ideal for growing businesses.

    Standout Features and Integrations:

    Features include log analytics, which help you query and analyze log data efficiently. Application insights provide end-to-end monitoring of your applications. The service also includes network performance monitoring to track and diagnose network issues.

    Integrations include Azure Automation, Azure Log Analytics, Azure Event Hubs, Azure Logic Apps, Azure Functions, Azure DevOps, Microsoft Graph, Power BI, and more.

    Pros and Cons

    Pros:

    • Supports hybrid cloud setups
    • Built-in log analytics tools
    • Native Microsoft Azure integration and observability

    Cons:

    • Limited visibility into non-Azure environments
    • Significant manual setup for dashboards and alerts
    Learn more about Azure Monitor:

Outras alternativas ao Datadog

Eis algumas alternativas adicionais ao Datadog que não entraram na minha lista restrita, mas que vale a pena conhecer:

  1. 11
    Dash0Best for AI-assisted troubleshooting
  2. 12
    SigNozBest for OpenTelemetry-native backend monitoring
  3. 13
    SentryBest for application error tracking
  4. 14
    Sumo LogicBest for cloud-native log analytics
  5. 15
    Better StackBest for incident response
  6. 16
    HyperDXBest for real-time debugging
  7. 17
    ChronosphereBest for cloud-native scale metrics

How I Evaluate Datadog Alternatives

I split my evaluation into two layers: core capabilities every tool must cover—unified metrics, logs, and traces—and the differentiators that make one platform a better fit than another.

Core Functionality (Table Stakes For This List)

When I'm selecting tools for my list, I rank each one on a scale from 0 (does not offer the functionality) to 5 (excels in this area) for each core functionality listed below. Then, I calculate the tool's total score into a percentage. Each tool needs to achieve a minimum total score of 75% to be considered for inclusion.

  • Full-Stack Observability: I look for unified metrics, logs, and traces with cross-pillar correlation, so you can jump from a spike in latency to the exact trace and log line without switching tools.
  • Infrastructure & APM Monitoring: Each tool should cover hosts, containers, and Kubernetes clusters alongside code-level application performance data like service maps and flame graphs.
  • Real-Time Alerting & Incident Response: I evaluate alert configurability and escalation paths, checking for multi-condition thresholds, anomaly detection, and integrations with tools like PagerDuty or Opsgenie.
  • Dashboards & Visualization: Custom dashboards matter, so I check whether you can build tailored views with drill-down widgets, template variables, and team-level sharing for different stakeholders.
  • Broad Integration Ecosystem: The platform should connect to major cloud providers, orchestration tools, databases, and CI/CD pipelines, with native OpenTelemetry support being a strong signal here.
  • Scalable Data Ingestion & Retention: I evaluate how well each tool handles high-cardinality, high-volume telemetry and whether retention policies are flexible enough to balance cost with long-term analysis needs.

Once I have a list of tools that meet this criteria, I consider what sets each platform apart.

Differentiating Factors (What Sets Vendors Apart)

Here's how I compare and contrast different vendors:

Standout Features

AI-powered root cause analysis is a big differentiator. When a Kubernetes pod starts crash-looping at 2 a.m., tools that surface probable causes automatically save your on-call team real time. Synthetic monitoring is another area I evaluate closely—scheduled API and browser checks catch outages before users report them. I also look at whether a platform extends into security with built-in SIEM or cloud security posture management, since consolidating observability and security reduces tool sprawl for teams already stretched thin.

Beyond Features

Pricing predictability is often the top reason teams explore Datadog alternatives, so I check whether a vendor's billing model avoids surprise overages on custom metrics or log ingestion spikes. Deployment flexibility matters too—some teams need self-hosted or open-source options to keep telemetry data within their own infrastructure. I also evaluate each platform's commitment to open standards like OpenTelemetry and Prometheus, since native support for these makes it far easier to migrate or avoid long-term vendor lock-in.

Porque procurar uma alternativa ao Datadog?

Embora o Datadog seja uma boa escolha como plataforma de monitorização na nuvem, existem vários motivos pelos quais alguns utilizadores procuram soluções alternativas. Poderá estar à procura de uma alternativa ao Datadog porque…

  • Precisa de opções de preços mais acessíveis
  • A sua equipa necessita de uma configuração e gestão mais simples
  • Precisa de uma melhor integração com ferramentas específicas
  • A sua empresa exige mais funcionalidades de personalização
  • Precisa de suporte para uma região geográfica específica
  • A sua equipa necessita de melhores controlos de privacidade dos dados

Se alguma destas situações se aplica a si, veio ao lugar certo. A minha lista inclui várias opções de plataformas de monitorização na nuvem mais adequadas para equipas que enfrentam estes desafios com o Datadog e procuram soluções alternativas.

Principais funcionalidades do Datadog

Eis algumas das principais funcionalidades do Datadog, para ajudar a comparar as soluções alternativas:

  • Monitorização da infraestrutura: Monitoriza métricas, contentores e redes para garantir que os seus sistemas funcionam corretamente.
  • Monitorização do desempenho das aplicações: Fornece informações sobre o desempenho das aplicações e a gestão de bases de dados para otimizar a experiência do utilizador.
  • Gestão de registos: Gere registos com funcionalidades como a análise de dados sensíveis para ajudar a manter a segurança e a conformidade.
  • Monitorização de utilizadores reais: Acompanha os percursos dos utilizadores e o desempenho da interface para melhorar a experiência digital.
  • Monitorização sintética: Simula interações dos utilizadores para garantir o tempo de atividade e a disponibilidade.
  • Monitorização da segurança: Disponibiliza deteção de ameaças em tempo real e gestão da conformidade para manter os seus dados seguros.
  • Gestão de serviços: Simplifica os fluxos de trabalho de resposta a incidentes e de gestão de casos para melhorar a eficiência operacional.
  • Capacidades de IA: Utiliza ferramentas de IA para a deteção de anomalias e a monitorização do desempenho dos modelos, proporcionando informações mais aprofundadas.
  • Monitorização sem servidor: Fornece informações sobre aplicações sem servidor para garantir um desempenho ideal.
Paulo Gardini Miguel
Paulo Gardini Miguel
Paulo is the Director of Technology at the rapidly growing media tech company BWZ. Prior to that, he worked as a Software Engineering Manager and then Head Of Technology at Navegg, Latin America’s largest data marketplace, and as Full Stack Engineer at MapLink, which provides geolocation APIs as a service. Paulo draws insight from years of experience serving as an infrastructure architect, team leader, and product developer in rapidly scaling web environments. He’s driven to share his expertise with other technology leaders to help them build great teams, improve performance, optimize resources, and create foundations for scalability.
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