Top 5 self-service BI solutions for Amazon Athena

What is Amazon Athena?

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL without installing or managing servers and clusters. Athena assists you in analyzing unstructured, semi-structured, or structured data stored in Amazon S3. You can use it to conduct ad-hoc ANSI SQL queries without aggregating or loading the data into the data warehouse. Athena works with Amazon QuickSight to visualize data quickly. It may be used to produce reports or study data using business intelligence tools or SQL clients linked through a JDBC or ODBC driver.

Why use self-service BI?

Traditional BI platforms often necessitate considerable technical expertise, which can result in data bottlenecks and delays in decision-making. It also focuses on strict control over data, limiting access to a small group of experts with the technical skills to use them effectively. This can create bottlenecks, as non-technical users often struggle to get the necessary insights. In contrast,

Self-service BI platforms empower end business users—those without technical backgrounds—to analyze data and create visualizations independently, without relying on technical teams. These platforms prioritize broad access to data, making it available to as many people as possible. By putting data at users' fingertips, self-service BI empowers everyone in the organization to analyze and visualize information independently.

Integrating Amazon Athena with business intelligence (BI) platforms significantly boost its functionality, allowing users to craft interactive dashboards and reports effortlessly. Various BI tools connect seamlessly with Amazon Athena, enabling analysts to visualize and analyze their data with minimal setup. On the other hand, self-service BI takes this a step further by empowering users to independently access, investigate, and present data.

Type of self-service BI tools

Self-service BI tools integrate perfectly well with Amazon Athena, leveraging its powerful data processing capabilities to deliver real-time insights and analytics.

I have categorized the alternatives into two main groups:

• Third-party tools
• Warehouse-native self-service BI tools

Warehouse-native analytics solutions represent a new wave in the product and marketing analytics landscape. These tools operate directly on your existing data infrastructure, such as Amazon Athena, allowing cost-efficient and real-time access to first-party data. However, they require careful data modeling and optimization to ensure optimal performance in cloud data warehouses.

This blog post will explore the top five self-service BI solutions that integrate seamlessly with Amazon Athena. I’ll detail how each tool connects to Amazon Athena and highlight their unique features to help you maximize your data analysis efforts.

Top 5 self-service BI tools detailed comparison

Amplitude

Amplitude is a leading product analytics platform that helps organizations transform raw user data into actionable insights. Amplitude provides a comprehensive view of how users interact with digital products by tracking user behavior and understanding customer journeys.

Pricing

MTU-based: MTU-based pricing charges organizations based on the number of unique users actively engaging with the product within a given month.

How do I connect to Amazon Athena?

As it is not a warehouse-native tool, two methods exist to connect Amplitude with Amazon Athena. The automated approach utilizes reverse ETL tools, facilitating seamless integration and real-time data access from your existing infrastructure. The manual method, on the other hand, involves exporting data from Amplitude to a local system before importing it into Amazon Athena. This process can be more time-consuming and requires careful management of data formats.

Pros

• Comprehensive Product Analytics: Amplitude is designed to help you turn raw user data into meaningful insights. Features like real-time analytics, user segmentation, retention analysis, and conversion tracking provide a holistic view of how users interact with your digital products.
• User-Friendly Interface: The platform offers an intuitive interface that makes it easy to analyze user behavior and understand customer journeys.
• Advanced Cohort Analysis and A/B Testing: Amplitude shines in cohort analysis, allowing you to segment users based on their behaviors. Its built-in A/B testing feature also enables you to experiment with different strategies to optimize marketing outcomes efficiently.

Cons

• High Costs: One significant drawback is Amplitude’s event-based pricing model, which can become expensive as your product scales. Companies often pay for unused events, and as their Monthly Tracked Users (MTU) grow, you receive the same features at a higher price.
• Complex Setup and Maintenance: Implementing Amplitude requires extensive planning and manual event tagging. This process can be time-consuming and resource-intensive, hindering your ability to respond quickly to changing business needs.
• Data Moving Challenges: Since Amplitude is a vertically integrated SaaS application focused on product-related event data, users often need to engage in time-consuming reverse ETL processes to analyze the complete customer journey. This can lead to fragmented analytics and a lack of holistic insights.
• No warehouse-native connection to Amazon Athena: Without a native integration, you may face challenges in maintaining data accuracy and timeliness, as you need to set up and manage additional data pipelines or use another reverse ETL tool.

Mitzu.io

Mitzu.io is a no-code warehouse-native analytics platform designed specifically for product, marketing, and revenue analytics. Like other warehouse-native tools, it enables users to query product usage data without knowledge of SQL or Python.

Pricing

Seat-based: This model charges based on the number of user seats or licenses allocated to an organization's individuals. Each seat typically corresponds to a specific user who can access the software, regardless of how often they use it.

How do I connect to Amazon Athena?

Mitzu.io employs a warehouse-native strategy that facilitates smooth integration with Amazon Athena, delivering a powerful blend of ready-made product analytics visualizations and advanced BI-style data exploration tools. By directly querying your Amazon Athena data warehouse, Mitzu.io removes the need for data duplication, granting real-time access to all your enterprise data for thorough analytics. Mitzu connects to Amazon Athena by using username/password authentication.

Pros

• Warehouse-Native Analytics with Automatic SQL Query Generation: It simplifies data analysis by merging product data with marketing and revenue insights directly from your data warehouse. It automatically generates SQL queries based on your inputs, so you don’t need extensive SQL knowledge to get valuable insights.
• User Journey, Funnel, and Retention Analysis: You can track user interactions across various touchpoints to gain insights into their journey, conversion rates, and engagement, helping you improve retention strategies and keep users engaged.
• Individual User Lookup, Segmentation and Cohort Analysis: It analyzes user behavior by creating cohorts based on pricing plans, company size, and location for a more tailored approach. It allows for targeted analysis and personalized strategies.
• Subscription Analytics (MRR, Subscribers): Mitzu.io stands out as the only tool among its competitors that can handle subscription analytics, providing you with insights into Monthly Recurring Revenue (MRR) and subscriber metrics.
• Coverage of supported types: It’s important to see what data types they can handle for warehouse-native applications. Mitzu also supports Arrays, Tulips, and the brand-new JSON type.

Cons

• Limited Brand Recognition: As a newer player in the analytics market, Mitzu.io may lack the brand recognition and trust that established competitors like Amplitude and Mixpanel have built over the years.
• Scalability Concerns: Mitzu.io may face challenges in scaling its infrastructure and support as its user base grows. This could impact performance and customer service responsiveness, particularly for larger organizations with complex data needs.
• No AI tool: Mitzu stands out with its no-AI approach—it doesn't rely on artificial intelligence to generate insights. This commitment allows users to trust the accuracy and transparency of their data, ensuring that all analyses are based on real, unaltered information.

Mixpanel

Mixpanel is a straightforward yet powerful traditional product analytics tool that enables product teams to track and analyze in-app engagement effectively. It provides a clear view of every moment in the customer experience, allowing you to make informed changes that enhance user satisfaction.

Pricing

MTU-based: MTU-based pricing charges organizations based on the number of unique users actively engaging with the product within a given month.

How do I connect to Amazon Athena?

Since Mixpanel isn't a warehouse-native tool, you'll need to employ a third-party solution to link your data to it. You can use reverse ETL tools, facilitating seamless integration and real-time data access from your existing infrastructure. Another manual strategy for loading data from Mixpanel to the Amazon Athena database is to create a schema where you will map each API endpoint to a table. You must periodically check Mixpanel for new data and repeat the previously described process while updating your currently available data if needed.

Pros

• No SQL Required: One of Mixpanel's standout features is its ability to explore data without SQL expertise. This accessibility allows you to easily set up metrics and analyze data without extensive technical training.
• Real-Time Insights: It provides live updates on user interactions, enabling teams to adapt and optimize their products based on current user behavior.
• Comprehensive Data Exploration: Mixpanel offers powerful data analysis capabilities, allowing you to dissect information and uncover meaningful trends and patterns effectively. These insights directly inform your product strategy. The platform's feature for setting up growth and retention metrics enhances your strategic planning process.

Cons

• High Cost: Mixpanel’s pricing model is a significant drawback, as it can become quite expensive as your business scales. While it offers a free tier, charges are based on monthly recurring revenue (MRR), potentially leading to steep costs for rapidly growing companies.
• Limited User Journey Features: Mixpanel may not be the best fit if your needs include guiding users through product features using behavior-driven triggers. Its focus is primarily on analytics rather than user onboarding.
• Insufficient Advanced Segmentation: The platform's segmentation capabilities may not be robust enough for organizations requiring more complex analytical frameworks. This limitation could hinder detailed insights into user behavior.
• No warehouse-native connection to Amazon Athena: Without a native integration, you may face challenges in maintaining data accuracy and timeliness, as you need to set up and manage additional data pipelines or use a reverse ETL tool.

PostHog

PostHog is an open-source product analytics platform that provides a wide range of tools for tracking user interactions, analyzing data, and gaining insights to improve user experience and product performance. It features event tracking, heatmaps, and feature flags, with its open-source and self-hosted capabilities being particularly good.

Pricing

MTU-based: MTU-based pricing charges organizations based on the number of unique users actively engaging with the product within a given month.

How do I connect to Amazon Athena?

Since PostHog is not a warehouse-native tool, you will need to utilize a third-party ETL or reverse ETL solution to connect your PostHog data to Amazon Athena. This process requires syncing your data through another tool that can effectively interface with Amazon Athena.

Pros

• Open-Source: PostHog's open-source nature allows for extensive customization, enabling you to tailor the platform according to your specific needs.
• Self-Hosted: The self-hosted option provides greater control over data privacy and security, which is essential for businesses with strict compliance requirements.
• Comprehensive Feature Set: PostHog includes various features, such as event tracking, session recordings, feature flags, heatmaps, and user cohorts, which offer valuable insights into user behavior.
• Cost-Effective: Being open-source means there are no licensing fees, making it an appealing choice for small to medium-sized businesses with budget limitations.
• Active Community: An engaged community supports continuous updates, feature development, and user assistance.

Cons

• Steep Learning Curve: Users unfamiliar with analytics platforms may initially find PostHog challenging to navigate, especially when configuring advanced features.
• Resource Intensive: Operating PostHog as a self-hosted solution can demand significant hardware and technical expertise, which may pose challenges for smaller organizations.
• Limited Integrations: Although PostHog integrates with popular tools, it is not warehouse-native, necessitating the use of third-party tools for data synchronization with BigQuery.
• Ongoing Maintenance: Self-hosted solutions require continuous maintenance, updates, and monitoring, which could be burdensome for teams with limited IT resources.

Pendo

Pendo is a product analytics tool that enables you to create improved software experiences that lead to happier and more productive users and employees. Pendo combines powerful software usage analytics with in-app guidance and user feedback capabilities, enabling even non-technical teams to deliver better product experiences to their customers or employees.

Pricing

MAU-based: MAU-based pricing charges organizations based on the number of unique users actively engaging with the product within a month.

How do I connect to Amazon Athena?

To connect Pendo data to Amazon Athena, you must utilize a third-party ETL or reverse ETL tool, as Pendo does not offer native integration. This requires setting up additional data pipelines to ensure accurate and timely data synchronization between Pendo and Amazon Athena.

Pros

• Comprehensive Product Insights: Pendo provides in-depth analytics that allows you to track user behavior across their applications.
• Integrated In-App Guidance: The platform enables you to create in-app messages and guides without coding, facilitating user onboarding and feature adoption.
• Robust Feedback Mechanisms: It includes tools for collecting user feedback through surveys and polls, allowing you to capture sentiment and insights directly from your users at crucial moments in their journey.
• Powerful Session Replay: The session replay functionality allows you to visualize user interactions within the app to find real customer feedback.
• Strong Community Support: Pendo is backed by an active community and resources like Mind the Product, offering training, events, and content to help product managers and teams improve their skills and knowledge.

Cons

• High Cost: Pendo's pricing can be steep, especially for small businesses or startups. As companies scale, the costs may become really high as they rely on MAU.
• Complex Setup and Learning Curve: While Pendo offers many features, setting them up can be complicated. New users may find it challenging to navigate the platform effectively, leading to a steep learning curve.
• Customization Challenges: Although Pendo is designed to be user-friendly, customizing the platform to meet specific business needs can be complex and may require technical expertise.
• Potential for Feature Bloat: As Pendo continues to add new features, there is a risk of feature bloat where additional functionalities may overshadow core capabilities, potentially complicating your experience.
• No warehouse-native connection to Amazon Athena: Without a native integration, you may face challenges in maintaining data accuracy and timeliness, as you need to set up and manage additional data pipelines.

Conclusion

This page provides a comparison of five self-service BI solutions designed for Amazon Athena:

• Mitzu.io is a warehouse-native tool that automatically generates SQL queries and specializes in subscription analytics. It is connected warehouse-natively to Amazon Athena and excels at analyzing user journeys and individual user lookups. Still, as a newer player in the market, it may face scalability challenges.
• Mixpanel is a robust product analytics solution that delivers real-time insights and extensive data exploration capabilities. It allows users to access analytics without needing SQL skills, but its pricing can be high for fast-growing companies. Additionally, Mixpanel requires supplementary reverse ETL tools to integrate with Amazon Athena.
• Pendo offers valuable tools for product analytics and enhancing user experiences. However, you should consider the complexities of integrating it with Amazon Athena through third-party solutions and the associated maintenance efforts required.
• PostHog is an open-source product analytics platform that enables businesses to track user interactions and make data-driven decisions effectively. However, as it is not a warehouse-native tool, users must rely on third-party solutions for data integration, adding complexity to data management while offering flexibility and control over user experience.
• Amplitude is a well-known product analytics platform recognized for its intuitive interface and powerful behavioral analytics capabilities. It supports advanced user segmentation and predictive analytics but can be complex for newcomers and potentially expensive for larger organizations. Like Mixpanel, Amplitude also requires additional reverse ETL tools to function with Amazon Athena.

Each solution offers unique advantages and drawbacks, with different pricing structures and integration capabilities. The best choice depends on your business requirements, technical skills, and scalability needs.