Best Embedded Analytics Tools for SaaS

Embedded analytics tools can transform SaaS platforms by integrating data visualization and AI-driven insights directly into applications. This guide breaks down seven popular tools, covering their integration options, AI features, scalability, security, and pricing. Here's a quick overview:

• Querio: API-driven, no iframes, AI insights, strong multi-tenancy, starts mid-five figures annually.

• Looker: Centralized data logic (LookML), iframe embedding, high cost (~$200K/year).

• Tableau: Strong visualizations, iframe embedding, $70/user/month for creators.

• Power BI Embedded: Azure integration, scalable pricing starting at $735/month.

• Sisense: Deep embedding, quote-based pricing (~$10K+ annually).

• Domo: Cloud-native, tiered subscriptions ($50K-$100K/year).

• ThoughtSpot: Search-driven analytics, conversational AI, custom pricing (~$25K/month).

Quick Comparison

Each tool has strengths and trade-offs. Querio stands out for its seamless integration and scalability, while Looker and Tableau are better for teams with specific enterprise needs. Power BI and Sisense offer flexible options for Microsoft users and advanced embedding, respectively. Domo and ThoughtSpot focus on ease of use and AI-driven insights, but come with higher costs.

Your choice depends on your SaaS platform’s technical needs, budget, and growth plans.

Embedded Analytics Tools Comparison: Features, Pricing, and Integration Options for SaaS

The Best Embedded Analytics Strategy Isn’t Just Build or Buy

1. Querio

Querio offers an embedded analytics platform designed specifically for SaaS applications. It handles everything from data ingestion to visualization, simplifying the complexities of integration. Let’s take a closer look at how Querio addresses key needs like integration, AI, security, and scalability - critical elements for any SaaS platform.

Integration and Embedding

Querio integrates seamlessly into your SaaS platform, avoiding the use of iframes for embedding. This gives you full control over the design and ensures that dashboards and charts align perfectly with your brand’s look and feel. Its comprehensive API suite allows you to build advanced features, such as workflow automation and predictive insights, directly into your application. Plus, its data engine processes structured and semi-structured data (like JSON and APIs) without relying on external ETL tools. This means you can create self-service dashboards and workflows with ease.

AI Capabilities

Querio empowers your SaaS application with AI-driven insights and machine learning capabilities. Through its API suite, you can embed predictive analytics and AI-assisted decision-making directly into customer-facing workflows. This makes your application smarter and more responsive, helping users make informed decisions effortlessly.

Governance and Security

Security is non-negotiable for SaaS platforms, and Querio delivers with multi-tenant security baked into its architecture. From day one, tenants are isolated, ensuring there’s no need for makeshift solutions as you scale. Granular access controls, including inheritance models, allow you to define access permissions once and apply them consistently across your entire customer base. This ensures robust governance without adding complexity.

Scalability and Performance

Querio’s Elasticsearch-backed data lake ensures consistent performance, even with thousands of concurrent users. The platform is built to scale without limits - whether it’s users, dashboards, or deployments. Running on a cloud-native infrastructure across AWS and Azure with Kubernetes containers, Querio guarantees high security, compliance, and reliability.

Pricing in USD

Querio operates on a flat-fee annual subscription model, typically in the mid-five-figure range, which covers unlimited users. Pricing is tailored to your specific deployment needs, helping you avoid unexpected per-user licensing costs as your customer base grows.

"My litmus test for analytics software is whether you can use it to drive insight/action that offsets the license & implementation cost of the tool – I think Querio is more than capable of this." - Dara K, verified Capterra user

2. Looker Embedded Analytics

Looker Embedded Analytics is a strong contender for Google Cloud users and data-heavy SaaS applications. Its standout feature is the LookML layer, which centralizes and version-controls data logic. This ensures that dashboards and reports remain consistent - a crucial factor for teams working with shared data definitions.

"The best part about Looker is its powerful semantic modeling layer (LookML), which enables centralized and version-controlled system." – verified g2 user

Integration and Embedding

Looker provides robust embed controls and an API that allows for deep integration into SaaS applications. Originally designed as a traditional BI platform, embedding capabilities were added later, relying on iframes for integration. While this approach works, it offers less design flexibility compared to platforms built specifically for embedding. Additionally, setting up and maintaining Looker often requires significant developer input, making it a better fit for teams with strong technical expertise.

AI Capabilities

Looker includes predictive analytics tools that help businesses make proactive decisions. These features allow SaaS companies to uncover forward-looking insights, giving users the ability to anticipate trends and make informed choices.

Governance and Security

When it comes to user-facing analytics, Looker provides solid security measures. It supports multi-tenancy setups, though implementing these can be more complex compared to platforms specifically designed for multi-tenancy. The centralized LookML modeling layer plays a key role in maintaining governance by ensuring consistent data definitions across tenants. That said, these features come with cost considerations that are worth noting.

Pricing in USD

Looker follows an enterprise licensing model, with costs for a full embed license exceeding $200,000 annually. This pricing structure has been criticized for being expensive and not scaling well for embedded use cases. For SaaS companies aiming to expand their embedded analytics across a growing customer base, these high upfront costs can be a major hurdle. Some potential customers might even dismiss the platform due to its steep price tag.

3. Tableau Embedded Analytics

Tableau Embedded Analytics is a robust choice for SaaS companies focused on delivering detailed data visualizations. Initially designed as an internal BI tool, Tableau has since expanded to include embedding capabilities for customer-facing analytics. By using its JavaScript API and iFrames, Tableau allows interactive dashboards to be embedded directly into web applications.

Integration and Embedding

Tableau primarily relies on iFrames and its JavaScript API for embedding. While this approach gets the job done, it comes with limitations in terms of design flexibility and customization. Unlike platforms specifically designed for embedding, Tableau's iFrame-based system can make seamless integration more challenging. Developers often need to invest extra effort to align the design with the rest of the application. Another challenge is the lack of native multitenancy, which means SaaS providers need to create custom solutions to ensure data isolation for different customer tenants, adding to the complexity of implementation.

AI Capabilities

On the AI front, Tableau offers features like integration with Einstein AI and Tableau Pulse, which enhance analytics capabilities. However, it falls short when it comes to user-friendly tools like a built-in query assistant, which can make the platform harder to navigate for those new to it.

Scalability and Performance

Tableau supports a wide range of data sources, offering both live connections and cached extracts. While this flexibility is a plus, the absence of native multitenancy creates challenges for data governance. Ensuring secure data separation between tenants often requires additional engineering work, adding another layer of complexity for SaaS businesses.

Pricing in USD

Cost can be a significant factor when considering Tableau for embedded analytics. A Creator license is priced at approximately $70 per user per month, while an Embedded Viewer license costs around $420 per user annually. For businesses looking to scale, these costs can quickly add up, potentially reaching into the high six figures annually.

4. Microsoft Power BI Embedded

For SaaS companies exploring embedded analytics tools, Microsoft Power BI Embedded offers a blend of integration options and flexible analytics features. It’s especially suited for organizations already using Microsoft services like Office 365 and Azure. With API-driven dashboard customization and enterprise-grade analytics, it’s a solid choice, though there are specific factors to consider when embedding.

Integration and Embedding

Power BI Embedded provides two main ways to embed analytics:

• iframes for embedding full reports

• Power BI JavaScript REST API for creating tailored applications or embedding specific visuals.

Your choice depends on the context - whether embedding is for internal users or external customers. Licensing and authentication vary based on this decision, so it’s crucial to establish the right setup. For external applications, secure credential management is a must.

Additionally, Power BI integrates seamlessly with the broader Microsoft Power Platform, including tools like PowerApps and Power Automate. This integration allows businesses to design cohesive, data-driven experiences, enhancing customization and connectivity across their analytics framework.

AI Capabilities

Power BI combines AI-powered insights with tools for data transformation, automation, and paginated reporting, making it a strong option for traditional business intelligence tasks.

Scalability and Performance

While Power BI is designed to handle enterprise-level analytics, it can face challenges under high concurrent usage. Multi-tenant environments often require additional custom development, and its capacity-based pricing model can make scaling tricky. Costs grow as capacity needs increase, which adds complexity to forecasting expenses.

Pricing in USD

Pricing begins at around $735 to $750 per month for A1 capacity, operating on a usage-based model. Costs are influenced by compute capacity and concurrency, which can lead to fluctuating budgets as usage patterns change.

5. Sisense

Sisense is an embedded analytics platform designed for SaaS businesses, offering the ability to handle complex data environments while keeping user interactions straightforward.

Integration and Embedding

Sisense excels at embedding dashboards and reports directly into SaaS applications, making integration relatively smooth. Its interface is intuitive for basic analytics, but creating advanced dashboards may require additional JavaScript, which can add some technical challenges. This robust integration framework also lays the groundwork for embedding AI capabilities that deliver actionable insights.

AI Capabilities

Sisense incorporates AI-driven tools to enhance decision-making. These tools work alongside standard analytics features, helping users identify patterns and insights that might otherwise go unnoticed in their data.

Scalability and Performance

Sisense uses in-chip analytics to process large datasets efficiently, ensuring quick results even with high data volumes. Features like caching and asynchronous loading help maintain speed as user demands grow. However, for the best performance - such as faster loading times - enterprise-tier subscriptions are often the better choice.

Pricing in USD

Sisense follows a quote-based subscription model, with costs typically covering both user and server licenses. Annual pricing starts at approximately $10,000. For enterprise-level plans, costs can climb into the mid-six-figure range annually, and for larger implementations, they may even reach millions. With costs increasing as more licenses and features are added, careful budgeting and planning are essential.

6. Domo

Domo is a comprehensive cloud-based business intelligence platform that combines data extraction, storage, and visualization in a single system. For SaaS businesses, it provides an embedded analytics feature that allows dashboards and reports to be directly integrated into your applications.

Integration and Embedding

With its cloud-native design and robust APIs, Domo makes embedding analytics straightforward. The platform manages everything on the backend - data processing, storage, and visualization - offering a streamlined deployment process. However, this convenience comes with a trade-off: you're tied to Domo's ecosystem.

AI Capabilities

Domo incorporates AI-driven tools that simplify data exploration, even for users without technical expertise. These features complement its standard analytics functions, helping users identify trends and patterns in their data with ease. Up next, it’s worth examining how Domo handles security in multi-tenant environments.

Governance and Security

When it comes to security, Domo has limited multi-tenant capabilities. If your SaaS application serves multiple clients who need strict data isolation, this is something to consider. While the platform does offer security measures, you’ll need to assess whether they align with your specific multi-tenancy needs.

Scalability and Performance

Domo is designed to scale automatically as your data and user base grow. Its infrastructure adjusts without manual intervention, reducing the operational burden and ensuring consistent performance.

Pricing in USD

Domo operates on a tiered subscription model based on credits and usage. Pricing depends on factors like the number of users, data volume, and refresh frequency. For mid-sized deployments, costs typically range between $50,000 and $100,000 annually, so careful financial planning is essential.

7. ThoughtSpot

ThoughtSpot is a search-driven analytics platform that simplifies data exploration by using natural language queries. This makes it an excellent choice for non-technical users who want to interact with data without needing to master complex query languages. Its standout feature is a conversational approach to analytics, recently enhanced with the integration of Large Language Models like Gemini.

Integration and Embedding

ThoughtSpot offers a high degree of customization, allowing you to seamlessly embed dashboards into your SaaS platform while maintaining your brand's look and feel. This level of integration strengthens the value of embedded analytics by enhancing the overall user experience. The platform supports secure multi-tenancy, though setting it up can require significant effort. For instance, a SaaS CRM platform reported a 25% increase in user engagement after implementing real-time, natural language query capabilities. ThoughtSpot’s AI features take this a step further, making data exploration even more dynamic.

AI Capabilities

The platform’s AI tools include anomaly detection and automated insights, which work seamlessly with its search-driven interface. This combination makes it easier for users - even those new to analytics - to uncover meaningful data patterns. By leveraging natural language queries, ThoughtSpot aligns with the growing trend of making analytics more accessible to everyone, spreading data-driven decision-making across organizations. Many users praise its AI-driven highlights for delivering insights that lead to actionable outcomes.

Scalability and Performance

ThoughtSpot is built to handle large datasets effectively, covering most business needs. However, performance can occasionally dip when managing extremely high data volumes. Additionally, resolving more complex technical challenges may take longer, especially when engineering support is involved.

Pricing in USD

ThoughtSpot offers custom pricing tailored to your specific deployment and usage needs, with options for both usage-based and user-based models. Previously, the platform was reported to cost $25,000 per month for unlimited users. For larger deployments, it’s important to account for these potentially high licensing fees when planning your budget.

Advantages and Disadvantages

After diving into detailed tool reviews, let’s summarize the key trade-offs you’ll need to weigh. Each tool comes with its own set of strengths and limitations. Purpose-built embedded analytics tools, for instance, often offer predictable pricing models and strong multi-tenancy support - features that are crucial for scaling SaaS products effectively.

Here’s a breakdown of the main pros and cons for each tool:

When considering scalability under heavy workloads, tools that automatically adjust resources are game-changers. These features help avoid performance bottlenecks as your user base grows. Additionally, pricing structures - whether per user, per query, or capacity-based - play a big role in determining how well a tool aligns with your growth strategy.

For multi-tenant SaaS environments, features like robust data isolation and automated provisioning are non-negotiable. Purpose-built tools often handle these complexities with less engineering effort, making them a solid choice for businesses aiming to scale efficiently.

Conclusion

Choosing the right embedded analytics tool depends on where your company stands today and where it's headed. For early-stage companies, keeping things simple and predictable is essential. Opting for fixed-price models can shield you from unexpected licensing costs as your user base expands.

For SaaS businesses in the growth phase, scalability becomes the top priority. If your product caters to multiple customers with separate data needs, strong multi-tenancy support can save your engineering team time and effort, allowing them to focus on enhancing core features. As businesses reach the enterprise level, the considerations grow more complex.

Enterprise companies need to look closely at integration, customization, and security. Tools like Querio shine here, offering AI-powered natural language querying and secure, real-time connections to platforms like Snowflake, BigQuery, and Postgres. These features ensure high performance while meeting the advanced requirements of larger organizations.

Pricing is another critical factor. Tools specifically designed for embedded analytics often provide more predictable costs compared to retrofitting traditional BI platforms for embedding.

In short, the best choice will depend on your technical capabilities, budget, and desired level of analytics integration. From startups to enterprises, finding a tool that balances seamless integration, advanced features, and predictable pricing is key to supporting your business's growth.

FAQs

What should SaaS businesses look for in an embedded analytics tool?

When selecting an embedded analytics tool for your SaaS platform, it’s important to look for tools that can integrate smoothly with your APIs and connectors, handle increasing data loads as you grow, and support multitenancy to ensure secure, tenant-specific data management. Think about deployment options too - whether cloud-based, on-premise, or hybrid - to match your existing infrastructure.

You’ll also want to explore tools that allow for branding customization, include AI-powered features for deeper insights, and offer an intuitive, easy-to-navigate interface to improve the experience for both your team and end users. Make sure to assess security features such as encryption and compliance with data privacy regulations, and look for pricing models that are flexible enough to fit your budget while scaling with your business needs.

How does Querio provide secure and scalable analytics for SaaS applications?

Querio provides a dependable analytics platform tailored for SaaS applications, built on a secure and scalable cloud-based architecture. It prioritizes data security with advanced features like multi-tenancy, encryption, and row-level security. These measures safeguard sensitive information while enforcing strict access controls to ensure only authorized users have access.

On the scalability front, Querio is built to adapt seamlessly to growing user demand. Its enterprise-level infrastructure delivers consistent performance, making it a trusted choice for fast-evolving, data-intensive environments.

What are the common pricing models for embedded analytics tools, and how do they affect SaaS businesses?

Embedded analytics tools generally follow four pricing models: seat-based, usage-based, feature-based, and fixed pricing.

• Seat-based pricing charges per user. While straightforward, this model can become costly as your SaaS user base expands.

• Usage-based pricing is tied to metrics like data volume or API calls, offering flexibility but potentially leading to unpredictable expenses.

• Feature-based pricing focuses on the features you select, making it a good choice for businesses with specific needs.

• Fixed pricing provides consistent costs, which many scaling businesses find easier to manage.

Choosing the right pricing model is a critical decision for SaaS companies. It affects everything from budgeting to scalability and cost control. Among these options, fixed pricing often stands out for its simplicity and ability to support long-term financial stability.

Related Blog Posts

• Ultimate Guide to Collaborative Data Visualization Tools

• Top embedded analytics tools for user-facing dashboards (2026)

• The Buyers Guide for Embedded Analytics Classifies and Rates Vendors

• Embedded Analytics Tools & Platforms Guide