12 Best Tableau Alternatives For Modern Data Teams

Tableau is a classic. As the old saying goes: No one ever fires you for choosing Tableau.

One way to think about Tableau is as a machine that turns data into insight, but as your organization’s needs evolve, that machine starts to sputter. At first, it’s all about the sleek visuals—beautiful charts and dashboards that make complex data look simple. But as your demand for deeper analysis grows, you’ll begin to run into limitations that make Tableau feel more like a bottleneck than a breakthrough.

In this blog post, we'll walk you through Tableau's limitations and analyze 12 Tableau alternatives, including Holistics, Looker, Sigma Computing, Sisense and more.

Tableau Limitations

Tableau is one of the most popular data analytics tools, famous for its advanced data visualization capabilities. If your company is looking for a BI product with fancy charts to present to your management or your board of directors, Tableau will always be the perfect choice.

(Did you know Tableau means "painting" in French?)

However, as your organization’s analytical needs evolve, pretty charts are no longer enough and you’ll likely run into these Tableau limitations.

1. Analytics Bottleneck at Data Team

Business users still depend on data analysts to create and maintain reports. As requests pile up, analysts end up as “English to SQL” translators, constantly fielding ad-hoc data queries instead of working on high-impact analysis. The promise of quick, self-service insights fades.

2. Limited Self-service Capacity

Tableau does not allow business users to customize their setup of dimensions and metrics in the reports they want. While users can easily explore pre-defined dashboards, they’re often stuck when they need to tweak dimensions or metrics themselves. If you don’t know SQL, you’re out of luck, and frustration grows.

3. Disparate Metric Definition

As more reports are created, it’s easy to accidentally recreate the same metrics with slight differences across dashboards.

Over time, this inconsistency becomes a headache for data teams, as maintaining accuracy and uniformity across reports turns into a never-ending task.

4. No Code Version Control

Since Tableau uses its own proprietary file formats, there’s no code version control/change process management. One person editing locally and pushing up can overwrite everyone else, making it difficult for a team to manage.

5. Declining Customer Support

Tableau once prided itself on exceptional customer support, especially in its early days. However, since the Salesforce acquisition, many users have reported a noticeable decline in support quality.

Whether it's bottlenecks at the data team, limited self-service capacity, or the lack of version control, many businesses find themselves outgrowing Tableau. Tools like Holistics and Power BI provide strong Tableau alternatives, each with its unique advantages depending on your company’s needs.

12 Tableau Alternatives For Modern Data Team

01. Holistics

Holistics is a self-service BI tool built with DevOps best practices. Holistics offers similar data visualization capabilities while innovating on what Tableau is lacking:

• Centralized data management and reusable data models.
• Git integration for version control and maintainable workflows.
• Non-technical users can explore data without writing SQL.

Pricing

Holistics’ pricing starts from $800/month, Holistics charges you based on your usage. It’s designed to scale affordably as you roll out analytics across your entire company, making it competitive in the BI landscape.

Pros:

• Self-Service Analytics: Business users can create their own charts and get actionable insights without needing SQL.
• Centralized Data Management: The tool features a code-based semantic layer where data teams can define reusable metrics, ensuring consistent reporting.
• Strong Customization Capabilities: With the Canvas Dashboard (Dashboard as Code), users can arrange building blocks to design customized layouts, reporting experiences, themes, and charts.
• Git Version Control: Track every change, branch, and perform code reviews to ensure a maintainable and accurate analytics workflow.
• Seamless Integration with dbt: Holistics integrates with dbt, allowing you to model and transform data at the dbt layer and push those definitions directly into the BI layer.
• Robust Data Delivery: Schedule and automate report delivery via Email or Slack, with password-protected shareable links for security.

Cons:

• Learning Curve for Data Modeling: To unlock Holistics’ full potential, users need to get comfortable with data modeling concepts. But the time saved on ad-hoc data questions down the line makes it worth it.
• AQL Learning Curve: Holistics’ proprietary Analytics Query Language (AQL) adds advanced data analytical capabilities but comes with a slightly steep learning curve for new users.

Related reading: BI Tools Comparison Matrix: A Holistic Collection (Updated)

02. Power BI

Power BI is another well-known business intelligence platform with strong modeling capabilities and rich visualizations. It is also the first choice for every company that has adopted the Microsoft eco-system.

Pricing

Power BI offers a free desktop version for personal use. For advanced features and cloud solutions, you’ll need to pay $9.99/user/month. For larger needs, dedicated cloud servers start at $4,995/month.

Pros:

• Connect to multiple data sources.
• Rich visualization marketplace where you can replace your Tableau visualizations.
• Mature data modeling capabilities: Power BI excels at creating complex data models, offering a comprehensive analytics experience.

Cons:

• The learning curve is quite steep. Data analysts need to learn DAX (Data Analysis Expressions) and Power Query M language to get the most out of Power BI.
• Power BI desktop isn’t available on Mac, which can be a problem for teams that rely on Apple devices. (That's why we wrote a post on how to use PowerBI on Mac devices).
• Power BI is your gateway drug into Microsoft’s ecosystem :)

03. Metabase

Metabase is an open-source business intelligence tool that makes analytics accessible to everyone without knowledge of SQL. Metabase lets you ask questions about your data and displays answers in formats that make sense, whether that's a bar graph or a detailed table.

Pricing

Metabase has two versions — on-premise and cloud. On-premise is free. Cloud version starts at $85/month.

Pros:

• Open-Source Flexibility: As an open-source tool, Metabase allows full customization to fit your organization's specific needs, offering flexibility that proprietary tools like Tableau don’t.
• Ease of Use: Metabase’s simple, intuitive interface allows non-technical users to easily query data and create dashboards without needing SQL expertise. Users can explore data through point-and-click questions, making data access more democratic.
• Quick Setup: Metabase is easy to deploy, whether self-hosted or in the cloud.

Cons:

• Limited Advanced Features: While Metabase is perfect for basic querying and reporting, it lacks the advanced analytics, deep customizations, and rich visualizations that tools like Tableau or Power BI offer.
• No Version Control: Unlike more advanced BI tools that integrate with Git for version control, Metabase doesn’t offer this capability. This can make collaboration and change tracking difficult in larger teams.
• Scaling Challenges: Metabase is excellent for small to medium-sized businesses, but larger organizations with complex data needs might find its performance and feature set limiting as they scale.

For more information on the limitations of Metabase and its alternatives, please check out our article here.

04. Sisense

Sisense is a business intelligence platform based in the US that drives more efficient decision-making by enhancing business applications, workflows and processes using AI.

Pricing

Sisense practices to ‘no-surprise’ pricing. This means that everything is included in your annual subscription plan and pricing is customized based on data volume and number of users. For accurate pricing, you need to contact Sisense.

Pros:

• Cloud or On-Premise Hosting: Sisense offers flexible deployment, whether your business prefers on-premise hosting or cloud solutions.
• Supports SQL and NoSQL: Sisense supports a wide variety of data connectors, making it easy to unify all of your data sources.
• AI-Powered Insights: Sisense’s AI capabilities deliver predictive analytics and deep data exploration automatically, helping uncover hidden trends in your data.

Cons:

• Sisense’s Elasticube modeling system can be difficult for average users, often requiring SQL knowledge to operate effectively.
• Unlike other competitors, Sisense doesn’t list pricing on its website, which can feel less transparent for potential buyers. It's also reported that Sisense is as expensive as Looker.
• Sisense can be resource-heavy on servers, and implementation may require support from a Sisense partner.

05. Qlik Sense

Qlik Sense is a cloud-based BI tool that uses AI to help users understand and use data more effectively. Qlik Sense operates with an associative QIX engine, enabling the user to link and associate data from varied sources and carry out dynamic searching and selections.

Pricing: Qlik Sense offers two packages:

1. Qlik Sense Business – Priced at $30/month, billed annually.
2. Qlik Sense Enterprise SaaS – Pricing for this version is customized, depending on the number of users and other factors, and is available upon contacting the sales team. The enterprise version can be either Qlik-hosted or client-managed, while the business version is only available as Qlik-hosted.

Pros:

• Integrated Data Connectors: Qlik supports numerous data connectors, with many built-in integrations that don’t require separate installations, making it easier to connect various data sources.
• Data Discovery for All Users: Features like data discovery allow non-technical users to generate and share insights easily, promoting a more data-driven culture within the organization.

Cons:

• Performance Issues with Large Datasets: Some users report slowdowns or errors when handling large datasets, particularly in the data load editor.
• Steep Learning Curve: Qlik Sense can be challenging to configure without prior training, and its complex UI may take time to navigate, especially for new users.
• Cost for Large Teams: The enterprise version can become costly for companies with many users, leading some to explore more affordable alternatives.
• Complex User Interface: The interface can feel overwhelming, with too many similar dropdowns and options, making it time-consuming for users to find simple features.

For more Business Intelligence recommendation, check out:

• 05 Best Self-Service BI & Analytics Tool
• Best Embedded BI Platforms + Evaluation Guide

06. Domo

Domo is a cloud-based platform that provides BI and visualization services as well as other products such as embedded analytics, data integration and app automation.

Pricing

Domo’s pricing is customized based on several components related to the usage of the platform, including data storage, data refresh rates, volume of data queries, and the number of users.

Pros:

• Open Cloud Platform: Domo’s open platform allows for extensive customization.
• Rich Data Visualization Options: With over 150 chart types and a variety of dashboard designs, Domo ensures that data representation is both interactive and visually engaging.
• 1,000+ Pre-Built Data Connectors: Users can easily connect to a wide range of data sources without the hassle of extensive configuration, making integration seamless.

Cons:

• Limited End-User Functionality: Most data manipulation requires ETL, and the lack of parameter functionality (available in Tableau) means more processes need to be hard-coded.
• High Cost for Large Teams: Domo can be expensive compared to competitors like Tableau, especially when scaling up user profiles.
• No Semantic Layer: Unlike Tableau and Power BI, Domo lacks a semantic layer, which limits its ability to handle complex data modeling without heavy customization.
  

07. Sigma Computing

Sigma Computing takes the familiar spreadsheet-like interface and merges it with powerful data analytics capabilities, offering a middle ground between Tableau's visualizations and more technical tools.

Pricing

Sigma Computing follows a customized pricing model based on your organization's size and usage needs. You’ll need to get in touch with their sales team for specific details, but it’s known to be more accessible for larger organizations looking to scale.

Pros:

• Spreadsheet-like Interface: Sigma’s intuitive interface resembles a spreadsheet, making it easy for non-technical users to explore and manipulate data without writing SQL.
• Real-time Collaboration: Multiple users can work together on data analysis in real-time, making collaboration within teams seamless and efficient.
• Scalable: Sigma scales effortlessly with your data as it grows, particularly in cloud-first environments.
• No Data Movement: Sigma doesn’t extract data into the tool itself but works directly within the data warehouse, ensuring faster queries and less complexity.

Cons:

• Limited Visual Customization: While Sigma excels at data exploration, it doesn’t offer the same depth of visual customization that Tableau does. Users looking for flashy or highly stylized charts might find Sigma’s offerings more basic.
• Learning Curve for Advanced Features: Although Sigma is great for basic data exploration, advanced users may still face a steep learning curve when utilizing its more sophisticated data modeling and analytics features.
• No On-premises Option: Sigma is strictly cloud-based, so organizations with on-premises data requirements will need to look elsewhere.

Sigma Computing shines as a Tableau alternative for organizations prioritizing data exploration and cloud-first strategies. Its ease of use for business users, combined with the power of live data analysis, makes it a strong contender for companies wanting to scale data access across teams without needing SQL expertise.

08. Lightdash

Lightdash is a relatively new open-source business intelligence solution that can connect to a user's dbt project to allow users to add metrics directly in the data transformation layer, and then create and share insights with their team.

Pricing

Lightdash has a free version that is based on open source. There is a cloud beta version that is targeted at startups/scaleups. There is also an enterprise level that is designed to cater to enterprises.

Pros:

• Open-Source Flexibility: As an open-source tool, Lightdash is incredibly adaptable, scalable, and cost-effective for teams looking for a customizable BI solution.
• Strong Community Support: The open-source nature of Lightdash ensures a vibrant, supportive community, especially for the free and cloud beta versions. The enterprise edition also comes with dedicated support for larger teams.
• Robust dbt integration.

Cons:

• Limited Data Connectors: Currently, Lightdash supports fewer data connectors than many other BI tools, though it is catching up as more integrations are developed.
• Technical Knowledge Required: To fully utilize Lightdash, users need some technical skills, particularly SQL. Metrics and dimensions must be defined in the dbt model before any exploration or visualization can take place.

09. Trevor.io

Trevor.io is a business intelligence software that allows you to build queries and visualize data to answer data questions. From simple look-ups (e.g. checking a specific user's orders) to performing complex analyses.

Pricing

Trevor.io offers a transparent pricing structure starting at $249/month for teams, with pricing scaling based on the number of users and features required.

Pros:

• Easy Setup and Integration: Trevor.io integrates with popular databases like PostgreSQL, MySQL, and Amazon Redshift, and its setup is quick and straightforward. Teams can get started without complex configurations or technical overhead.
• Self-Service for Non-Technical Users: Trevor.io is built with simplicity in mind, allowing non-technical users to create custom queries, reports, and dashboards without writing SQL.
• Custom Alerts and Scheduled Reports: Business users can set up custom alerts based on specific data changes and schedule reports to be delivered via email, keeping teams informed without the need for manual checks.
• Live Training and Onboarding: Every new subscriber gets access to free, live training sessions, making it easier for teams to hit the ground running.

Cons:

• Limited Advanced Analytics: While Trevor.io excels at self-service reporting, it lacks some of the advanced analytics and visual customization features that Tableau and other BI tools offer. It's primarily designed for basic to intermediate data exploration rather than complex data modeling.
• Fewer Customization Options: Trevor.io’s dashboard and visualization options, while effective, aren’t as customizable or feature-rich as Tableau’s. Teams requiring highly customized or sophisticated visuals may find its options limiting.

10. Luzmo

Luzmo (formerly known as Cumul.io) is a robust alternative to Tableau, particularly if you're looking for a solution that specializes in embedded analytics. Luzmo’s platform allows businesses to embed interactive dashboards directly into their applications, giving end-users the ability to explore data seamlessly.

Pricing

Luzmo offers flexible pricing plans based on usage and customization needs, starting from $995/month.

The pricing model depends on factors like the number of embedded users and data volume.

Pros:

• Embedded Analytics Focus: Luzmo excels at embedding fully interactive dashboards into web applications, making it a great choice for SaaS platforms and product teams that want to provide data-driven insights to their end users.
• Highly Customizable Dashboards: Luzmo offers extensive customization options, allowing developers to design dashboards that blend perfectly into their existing products. From white labeling to complete layout control, it’s built to be flexible.
• Ease of Use for Non-technical Users: Even though it caters heavily to developers, Luzmo's intuitive interface allows business users to create and manage dashboards without needing technical expertise.
• Low-code Integration: Luzmo's low-code platform makes it easy to integrate with existing applications. You don’t need extensive coding experience to set up and manage dashboards, making it appealing for teams with limited development resources.

Cons:

• Limited Standalone BI Features: Luzmo shines in embedded analytics, but for teams looking for an all-in-one BI tool with extensive standalone reporting capabilities like Tableau, it might not be the best fit.
• Lacks Advanced Visualizations: While Luzmo covers most standard visualization needs, it doesn’t offer the same depth and variety of visual customization found in more mature BI tools like Tableau.

Luzmo is an ideal choice for companies that need embedded analytics without sacrificing ease of use and customization. It stands out as a dynamic Tableau alternative for SaaS platforms and organizations looking to integrate powerful analytics directly into their products.

11. Looker

Looker, now part of Google Cloud, is a modern BI platform that stands out for its powerful data modeling capabilities and integration with cloud infrastructures.

Unlike Tableau, Looker is designed to give data teams more control over how data is defined and accessed across the organization, using its LookML language.

Pricing
Looker follows a customized pricing model, which depends on factors like the number of users, scale of data, and integration needs. It is generally considered a more premium-priced tool, reflecting its enterprise-level features and robust integrations with Google Cloud.

Read more: Looker Pricing: How Expensive It Really Is?

Pros:

• LookML for Centralized Data Modeling: Looker’s LookML language allows data teams to define metrics and dimensions centrally, ensuring that business users are working with accurate, consistent data across all reports and dashboards. This eliminates the common issue of disparate metric definitions.
• Scalability and Performance: As a cloud-native tool, Looker easily scales with your data. It’s built to handle large datasets and complex queries without slowing down, especially when integrated with Google’s cloud infrastructure.

Cons:

• Steeper Learning Curve: Looker requires a deeper understanding of data modeling and its proprietary LookML language. For non-technical users, this can present a learning curve, requiring collaboration with data teams to build the foundation.
• Pricing: Looker is typically priced higher than other BI tools, making it a significant investment for companies. Smaller organizations may find it cost-prohibitive compared to alternatives like Power BI or Holistics.

12. Rill Data

Unlike other Tableau alternatives in this list, which excel in static data visualization, Rill Data is built to handle high-velocity data, making it an ideal alternative for companies that need to make decisions based on live data streams.

Its focus on simplicity, speed, and scalability makes it a strong contender for organizations in industries where real-time insights are crucial, such as finance, retail, and telecommunications.

Pricing
Rill Data offers a flexible pricing model based on the scale of data and query performance. Companies can reach out for a tailored quote, making it accessible for both smaller teams and larger enterprises that need to scale real-time analytics.

Pros:

• Optimized for Real-Time Analytics: Rill Data is specifically designed to handle high-velocity data, offering near-instantaneous insights from streaming sources. This makes it ideal for use cases where delays in data processing could lead to missed opportunities.
• Highly Scalable: The platform is built to scale easily, whether you’re dealing with millions or billions of data points. It ensures consistent performance even as data volumes increase.
• Simplicity and Speed: Unlike some BI tools that require extensive configuration, Rill Data is designed for simplicity. Its interface is intuitive and easy to use, allowing users to generate insights quickly without needing a deep technical background.
• Focus on Query Performance: Rill Data is optimized for fast query performance, reducing the time it takes to get answers from large datasets. This makes it an excellent tool for teams that need to process large amounts of data in real-time.
• Integration with Streaming Data Sources: Rill Data integrates seamlessly with streaming data platforms like Apache Kafka and Amazon Kinesis, ensuring that businesses can analyze data as it flows, without any delays.

Cons:

• Limited Advanced Visualizations: While Rill Data excels at real-time data handling, its visualization capabilities are more basic compared to Tableau or Power BI. It’s focused more on performance and speed than on creating complex or highly customized visuals.
• Niche Use Case: Rill Data is best suited for organizations that need real-time insights. For teams that primarily work with static or batch data, it might not offer the same value as a more traditional BI tool.
• Less Established in the Market: As a relatively new player in the BI space, Rill Data doesn’t yet have the same brand recognition or widespread adoption as Tableau, which may be a consideration for larger, more risk-averse enterprises.

Conclusion

All the Tableau alternatives mentioned above come with their own unique benefits and drawbacks. Choosing the right one for your company depends on various factors, such as the size of your organization, your data maturity, budget, and most importantly, the specific use cases you need to address.

This isn’t a decision you can make in a day. I recommend involving all relevant stakeholders—both data builders and data consumers—so you can thoroughly outline your requirements. From there, narrow down your options to the top 4-5 tools, and take the time to test each one.

For more guidance on choosing the right tool, check out Chapter 4 of our Analytics Setup Guidebook, where you’ll find a detailed breakdown of how to navigate the Business Intelligence tool landscape.