Top 5 self-service BI solutions for Snowflake

Snowflake is a powerful cloud-based data warehousing platform that enables organizations to manage and analyze vast amounts of data efficiently. With its unique architecture, Snowflake allows for seamless scalability and flexibility, making it an ideal choice for businesses looking to harness the full potential of their data.

One of Snowflake's standout features is its ability to separate computing and storage, allowing users to scale resources independently based on their workload needs. Snowflake’s support for diverse data types and formats enables you to ingest structured and semi-structured data effortlessly.

What is 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 need help to get the necessary insights. 

Self-service BI platforms empower end business users 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 Snowflake with self-service Business Intelligence (BI) tools further enhances its capabilities, enabling users to create interactive dashboards and reports easily. A wide range of self-service BI solutions seamlessly connect to Snowflake, allowing data analysts to visualize and analyze data without complex setups. These tools enable users to access, analyze, and visualize data independently—without relying on data analysts or IT teams—empowering them to make informed decisions quickly and effortlessly.

The alternatives can be categorized into two groups:

• Third-party applications
• Warehouse-native self-service analytics tools

Warehouse-native analytics solutions are a recent addition to the product and marketing analytics market. They operate directly on your existing data infrastructure, such as data warehouses—in this case, Snowflake. These solutions offer two main advantages: cost efficiency and real-time access to first-party data. However, their primary drawback is the need for careful data modeling and optimization to ensure swift performance in cloud data warehouses.

This blog post will explore the top five self-service BI solutions that work exceptionally well with Snowflake. We’ll detail how each tool connects to Snowflake and highlight the unique features they offer 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 Snowflake?

Traditionally, analyzing behavioral and financial data has been disjointed, with enterprise data residing in Snowflake and behavioral data in Amplitude. Snowflake-native Amplitude marks the first release for Amplitude under the Warehouse-native Amplitude umbrella. This new zero-copy solution enables Snowflake users to leverage Amplitude to perform powerful product analysis directly in Snowflake, bringing the application directly to their data.

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.
• Deliver powerful insights your teams can trust—as a service.: On the IT side, you can enable teams to directly find, understand, access, and activate the insights they need to drive your business forward.
• 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.

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 Snowflake?

With Snowflake-native Mitzu.io, you don't need to export data or build new data pipelines. It runs SQL queries directly on the data in your Snowflake account, providing insights straight from your source of truth. This process eliminates the need to move data between systems, minimizing data drift—the divergence of two datasets over time. It also helps your team reduce costs by maintaining and managing all your data directly in Snowflake.

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 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 Snowflake?

Third-party ETL tools simplify the data transfer process when connecting Mixpanel to Snowflake. First, set up Mixpanel as a source connector in your chosen ETL tool by entering your Mixpanel API credentials and selecting the data you want to replicate. Next, configure Snowflake as the destination by providing your Snowflake account details, including the database name, username, and password. After establishing the connections, schedule regular syncs to ensure that your Mixpanel data is continuously updated in Snowflake.

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.
• No warehouse-native connection to Snowflake: 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.
• 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.

Netspring

NetSpring leverages Snowflake's AI Data Cloud for Product and Customer Journey Analytics, utilizing Snowflake's centralized storage and compute engine to provide cost-effective, reliable, and impactful analytics to enterprises. Unlike traditional product analytics tools that rely on data copies outside the enterprise's central warehouse or data lake, NetSpring operates directly on data within Snowflake, eliminating the need for data duplication.

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 Snowflake?

NetSpring's native warehouse capabilities allow for seamless connection to Snowflake, enabling efficient data ingestion and analysis directly from your Snowflake environment. This native integration lets you combine product analytics with other enterprise data, providing enhanced insights.

Pros

• Self-Service: Access a rich library of product analytics reports and easily switch between reports and ad hoc visual data exploration to find answers to your questions.
• Warehouse-Native: Integrate product instrumentation with any business data in your data warehouse for comprehensive, context-rich analysis.
• SQL Option: This option simplifies funnel and path queries without requiring complex SQL while still allowing for the use of SQL for specialized analyses.
• Product and Customer Analytics: Utilize solutions for behavioral analytics, marketing analytics, operational analytics, customer 360 views, product 360 insights, and SaaS product-led growth (PLG) strategies.

Cons

• Limited Brand Recognition: As a newer entrant like Mitzu.io in the analytics market, NetSpring may lack the brand trust and recognition that established competitors possess, which could deter some potential customers. Optimizely has also acquired it, so the future strategy is still unknown.
• Learning Curve for Non-Technical Users: While NetSpring is designed for self-service, users without technical backgrounds may still face challenges in fully utilizing all of its features.
• Feature Limitations Compared to Established Competitors: While offering essential analytics capabilities, NetSpring may not have as many advanced features or integrations as the other platforms.

Kubit

Kubit is an analytics platform that enables companies to gain valuable customer insights without the need to move their data into silos. This warehouse-native approach reduces ownership costs, conserves engineering resources, and provides more accurate and comprehensive self-service insights.

Pricing

Flat-pricing: Kubit charges you based on their given flat price. The price is based on Monthly Tracked Users (MTU), with tiers at 10K, 1M, and 5M users. Pricing changes according to these tiers.

This information might be outdated as Kubit doesn’t openly state their pricing.

How do I connect to Snowflake?

As a warehouse-native tool integrated with Snowflake, Kubit generates native SQL queries directly on the company's Snowflake data warehouse, eliminating the need to duplicate product usage data. By partnering with Snowflake, Kubit ensures seamless integration and optimal performance, empowering teams to gain actionable insights from their data quickly and effectively.

Pros

• Efficient Analytics: Kubit provides real-time insights and powerful analytics capabilities, enabling organizations to make data-driven decisions quickly.
• Quick Setup: Kubit can be set up rapidly, allowing businesses to start analyzing their data without extensive delays or complex configurations.
• Scalable Options: The platform is designed to scale with your business needs, accommodating growing data volumes and user bases without significant performance degradation.
• Collaboration Features: The platform includes tools for sharing insights across teams and facilitating collaboration between product, marketing, and data teams to drive informed decision-making.

Cons

• Lacks Integrations: Kubit may have limited integrations with other tools and platforms, which could hinder its ability to fit seamlessly into existing workflows.
• Data Caps for Flat-Pricing: Some pricing tiers may impose data caps, restricting the amount of data that can be analyzed or stored, which could be a limitation for data-intensive organizations.
• Basic Features - limitations: While Kubit offers essential analytics functionalities, it may lack some advanced features in more established platforms, limiting its capabilities for sophisticated analysis.
• Steep learning Curve: Although designed for self-service, some users, particularly those not data-savvy, may still face a learning curve when trying to utilize all of Kubit's features effectively.

Conclusion

This page compares five self-service BI solutions for Snowflake:

• Mitzu.io is a warehouse-native tool for Snowflake that automatically generates SQL queries and offers subscription analytics. It shines in analyzing user journeys and looking up individual users. However, as a newer entrant, it might encounter scalability issues.
• Mixpanel is a powerful product analytics tool offering real-time insights and comprehensive data exploration. While it provides accessible analytics without SQL knowledge, its pricing model can be expensive for rapidly growing companies. However, Mixpanel requires additional reverse ETL tooling to work with Snowflake.
• Netspring is a cutting-edge platform offering self-service analytics and SQL options. It provides rich product analytics reports, and NetSpring operates directly on data within Snowflake, eliminating the need for data duplication. While powerful, it may present a learning curve for non-technical users.
• Kubit: A warehouse-native platform providing efficient analytics, quick setup, and scalable options. Despite its strengths in real-time insights, it may lack some advanced features and integrations compared to established competitors.
• Amplitude is a comprehensive product analytics platform known for its user-friendly interface and powerful behavioral analytics. It offers advanced user segmentation and predictive analytics but can be complex for beginners and potentially costly for larger organizations. The new zero-copy solution enables Snowflake users to leverage Amplitude to perform powerful product analysis directly in Snowflake, bringing the application directly to their data.

Ultimately, the best choice depends on your specific needs, technical expertise, and budget constraints. When deciding, consider factors such as ease of use, scalability, integration capabilities, and pricing models. Pay special attention to warehouse-native solutions like Mitzu.io, Amplitude, NetSpring, and Kubit for seamless integration with Snowflake.