Analytics Compare

Head-to-Head

Amplitude vs Matomo

This site is reader-supported. We may earn a commission if you purchase tools through our links.

Full category matrix: Product Analytics

Data last reviewed:

Amplitude Visit Website ↗
Matomo Visit Website ↗
Priority
Custom Event & Parameter Tracking
Bypasses typical event tracking limitations by allowing for highly customizable event schemas that adapt to unique data structures. However, the configuration complexity may necessitate dedicated engineering resources to ensure accurate deployment. By employing custom event tracking, Matomo enables the detailed monitoring of user interactions, facilitating granular insights into behavior patterns. That said, additional setup may be required for complex tracking scenarios to ensure exhaustive data capture.
10
Funnel & Drop-off Analysis
Funnel analysis tools enable the visualization of user journeys through defined paths, highlighting conversion rates at each stage. While these tools provide extensive insights, initial setup can be complex, requiring precise configuration. By analyzing user journeys through funnel analysis, Matomo enables the identification of drop-off points and optimization opportunities within conversion paths. That said, additional configuration may be required to accommodate complex funnel structures and ensure accurate tracking.
10
E-commerce Tracking
With features that enable monitoring of transaction data, digital storefront analysis is accomplished, though full insights may demand extra tools. Granular insights into e-commerce performance are enabled by Matomo's tracking capabilities, which support detailed analysis of sales and conversion metrics. However, integration with external systems may be necessary to fully utilize these capabilities and ensure exhaustive data capture.
10
Identity Resolution
Proprietary datasets support precise identity resolution, enhancing data accuracy despite potential integration complexities. Enhancing user analytics accuracy relies on the consolidation of identities across sessions and devices through proprietary methods.
10
GDPR / CCPA Compliance
Compliance features ensure adherence to GDPR and CCPA regulations, providing necessary data protection protocols. However, flexibility in customizing compliance settings may be limited, requiring standard configurations. By ensuring compliance with GDPR and CCPA, Matomo provides tools for managing user consent and data privacy, aligning with regulatory standards. However, ongoing updates may be required to maintain compliance as regulations evolve.
10
Mobile app analytics
Mobile analytics features enable the tracking of user interactions within mobile applications, providing key insights into app performance. However, the granularity of data may be limited, affecting the depth of analysis. By deploying mobile app analytics, Matomo supports the tracking and analysis of user interactions within native applications, providing insights into app performance and user engagement. In practice, additional SDK integration may be necessary to fully utilize this feature's capabilities.
10
Audience Segmentation
By deploying sophisticated algorithms, the system allows for detailed audience segmentation based on behavioral data. While these capabilities are extensive, they require complex configuration and may necessitate additional engineering resources. Native audience segmentation capabilities facilitate granular targeting by utilizing custom dimensions and attributes. However, the complexity of manual configuration demands considerable engineering resources.
10
Cookieless Ping / Consent Mode
Proprietary technology within Matomo's cookieless ping feature enables tracking without relying on cookies, ensuring compliance with privacy regulations. That said, additional configuration may be required to achieve efficient performance in diverse deployment scenarios.
9
Path Exploration / User Flows
Path exploration tools enable the visualization of user journeys across multiple interaction points, revealing detailed behavioral patterns. While these tools offer extensive insights, initial setup can be complex, requiring precise configuration. Enables detailed path exploration by processing sequential interaction data to visualize user journeys. In practice, the resource-intensive nature of handling large data sets can impact performance.
9
Cohort & Retention Analysis
Cohort analysis functionality enables detailed tracking of user groups over time to identify behavioral trends. While the analytical depth is extensive, the complexity of initial setup may present challenges for some configurations. By integrating cohort analysis, Matomo enables the examination of user behavior over time, facilitating insights into retention and engagement trends. However, the integration of additional data sources may be required to fully utilize the feature's capabilities.
9
Attribution Modeling
Contrary to basic attribution systems, Matomo provides customizable models that allow for detailed path analysis and conversion tracking, enhancing the accuracy of marketing performance assessments. However, configuring these models to fit specific organizational needs may necessitate additional engineering resources.
9
Raw Data Export (BigQuery/S3)
Unlike standard export functionalities, raw data export in Amplitude supports native integrations with data warehouses, facilitating native data transfer. While this capability provides direct access to raw data, limitations may exist in terms of export destinations or data formatting options. In contrast to basic export functions, Matomo's raw data export provides exhaustive access to all collected data, supporting detailed analysis and reporting. That said, additional data handling capabilities may be necessary to manage and process the exported datasets effectively.
9
Native SDKs
Native SDKs support the integration of analytics capabilities directly within mobile and web applications. In practice, these SDKs offer reliable functionality with minimal integration hurdles, enhancing application analytics. By providing native SDKs, Matomo facilitates native integration with mobile and web applications, supporting exhaustive tracking across platforms. That said, additional configuration may be necessary to optimize SDK performance for specific environments.
8
Data Sampling Control
Proprietary sampling methods in Matomo allow for handling large datasets by providing configurable sampling options, which can aid in maintaining performance during analysis. In practice, additional controls may be necessary to ensure precise reporting and avoid data distortion.
8
Proxy Deployment / Custom Domain
By supporting proxy deployment, Matomo allows for installation on customer-controlled infrastructure, including behind proxies and reverse proxies. In practice, significant technical expertise may be required to configure and maintain these deployments effectively.
8
Data Retention Limits
Data retention policies within the platform dictate the duration for which data is stored, aligning with compliance standards. Crucially, the length of retention is often contingent upon subscription level, potentially limiting historical data access. Different from basic data retention policies, Matomo offers configurable retention settings that align with various compliance requirements, allowing for tailored data management strategies. While the feature supports a range of retention scenarios, additional policy management may be necessary to ensure full compliance with organizational and regulatory standards.
8
Custom Dashboard Builder
Custom dashboard tools provide flexibility in visualizing data with various widgets and layouts. However, certain complex customizations may be limited by the platform's predefined templates. Granular customization within Matomo's dashboard builder allows for the creation of tailored analytics interfaces, supporting diverse reporting needs. However, significant customization efforts may be necessary to fully realize the potential of this feature.
7
Real-time Reporting
By enabling real-time reporting, Matomo provides immediate insights into user interactions, facilitating timely decision-making and response strategies. However, additional configuration may be necessary to optimize performance and ensure data accuracy in high-traffic environments.
7
Custom Data Models
Custom data modeling allows for the creation of specific analytical frameworks tailored to organizational needs. However, the complexity of these models can require substantial expertise to implement effectively. Contrary to rigid data models, Matomo's custom data models provide flexibility through the use of custom dimensions, events, and goals, adapting to varied analytics requirements. In practice, extensive manual configuration is often necessary to implement these models effectively.
7
Automated Schema Management
Proprietary schema tools automate the management of data structures, reducing manual intervention. However, certain complex configurations still require manual oversight to ensure data integrity.
7
Built-in A/B Testing
Native A/B testing modules facilitate the deployment of experiments directly within the platform. In practice, configuring complex experiments may require additional technical expertise and resources. Granular control over A/B testing in Matomo allows for the execution of detailed experiments, facilitating the optimization of user experience through data-driven decisions. While the feature supports a wide range of testing scenarios, setting up complex experiments may require additional configuration and technical expertise.
7
Bot Filtering
Through configurable bot-filtering mechanisms, non-human traffic is systematically excluded from analytics reports. While effective, maintaining accuracy necessitates frequent updates to bot lists.
6
Anomaly Detection
Bypasses standard limitations by the system integrates AI-driven insights for detecting anomalies in user behavior patterns. That said, real-time anomaly detection is restricted to higher-tier subscriptions.
6
Predictive Analytics (Churn/LTV)
Granular logs support predictive analytics by enabling the generation of predictive models that anticipate future user behaviors. However, extensive data preparation and model training are often required to achieve accurate predictions.
6
SSO Support
SSO support features facilitate secure access management through single sign-on integration. While these features enhance security, integration complexities may arise, requiring detailed configuration. Proprietary integration methods in Matomo's SSO support facilitate secure user authentication across platforms, enhancing access management capabilities. In practice, additional integration efforts may be necessary to ensure compatibility with specific identity providers.
6
Platform SCORE

Amplitude

5.4 / 10

Matomo

6.8 / 10

Where Amplitude and Matomo differ

Amplitude documents 19 supported capabilities; Matomo documents 22. Unique coverage below links to each feature hub.

Only in Amplitude

Only in Matomo

Make your pick: Amplitude or Matomo

JP

Jakub Pajtinka

Lead Data Curator

Jakub analyzes official documentation, evaluates data processing limits, and aggregates real sentiment from data engineering communities to build objective analytics software comparisons without the marketing fluff.

Connect on LinkedIn →

More Amplitude and Matomo matchups

Related categories

Explore these features