In a world where making real-time, data-driven decisions is increasingly important, it’s no surprise you want to invest in the best solution for your data and analytics operation. But with so much noise in the market, how can you truly know which provider is best for your business?
This article will break down the most impactful features of Looker vs Tableau, offering you an in-depth value comparison of these popular BI platforms.
Looker is Google Cloud Platform’s data exploration tool—specifically used for reporting and dashboarding. Acquired by Google in 2019, Looker uses a proprietary modeling language called LookML, which allows users to define and manage data models and metrics in a structured way. Additionally Looker includes a semantic layer built on LookML, enabling businesses to manage metric definitions through Looker Modeler.
Tableau is a legacy business intelligence tool launched in 2003, known for offering a vast library of pixel-perfect data visualizations. Because of its long-standing history and the functionality that allows analysts to prep raw data for visual consumption, it’s long been a favorite tool among technical users. Tableau was acquired by Salesforce in 2019.
Although Looker and Tableau are both business intelligence tools, they offer different benefits. For instance, Looker’s LookML allows users to build data quality and governance into their data models and utilize that semantic layer across their data ecosystem. Meanwhile, Tableau is well known for its visualization capabilities. Comparing Looker vs Tableau and understanding the core differences in these products will help you decide which solution is best for your business.
Looker’s browser-based solution offers a code-first environment for data governance and business analytics. Using its proprietary, SQL-based language—LookML—analysts can build data quality into their data visualization. Additionally, Duet AI promises to generate LookML code using natural language.
Looker integrates with most SQL-based platforms whether they are on-premises, like MySQL or Microsoft SQLServer, or cloud data platforms—think SQL Azure, BigQuery, Amazon Redshift, and Snowflake Data Warehouse and Amazon Athena.
Building data visualizations is a large part of Tableau’s user experience. Users can also use Tableau Prep, a data prep feature that allows analysts to organize data for visualization. Tableau’s newly announced Einstein 1 promises a host of AI tools that will offer users new ways to interact with their data.
Tableau connects with ODBC/JDBC based databases much like Looker, but they also connect with many Software as a service (SaaS) providers like Salesforce, Shopify, Marketo, GoogleAds, and other API based platforms. At its core, Tableau was designed to extract data from the data sources and on a server. Tableau also provides live queries to some data sources.
Now, let’s compare Looker vs Tableau in terms of visualization. Looker offers a number of native visualization options including pie charts, maps, and progression charts, however users have limited ability for customization. Their dynamic dashboard filter allows users to find specific types of visualizations. Business users can also utilize drag-and-drop features to configure data visualizations, and their mapping feature aids in chart creation.
Although Looker offers several visualization types, users may find its visualizations are not as comprehensive, visually appealing, or user-friendly when compared to its competitors. It’s worth noting that Looker’s visualizations are tightly coupled with LookML, enabling users to quickly identify dimensions, attributes, and measures.
When it comes to more advanced data visualizations, Tableau is a clear leader. Its easy-to-access visualization library helps technical users consume prepared data through a variety of visual representations in a drag-and-drop format. Tableau’s ease of use and ability to connect to various data sources makes it a good choice if you want to quickly create visualizations. However, it falls short when there is a need for additional data modeling.
Both Tableau and Looker curb users’ ability to limitlessly drill down into the data and unlock insights, creating additional work on data teams to model and prep data in order to answer the next question.
Looker is known for its ability to handle enterprise-scale data while also ensuring strict data governance with LookML. This model allows users to have more trust in the quality and accuracy of their data. However, a rigid governance layer can impede speed and agility for companies with dynamic data environments.
LookerML makes it easier to maintain consistency in your reports and dashboards, as changes to the data model automatically propagate to all related reports. In contrast, Tableau’s calculated fields and data prep may not offer the same level of well-modeled and well-governed data.
Tableau is strong for technical users who need advanced analytics and data-science-centric use cases like clustering, trend analysis, and more. However, visualizations built in Tableau are also built from static data models, which makes iterative and ad hoc analysis time-consuming for data teams.
But with the up-front feature complexity in both Tableau and Looker, it can be difficult for the average business user to find what the insights they are looking for—let alone feel confident using the tool for day-to-day decision making.
LookML supports git-integrated version control systems like Git, enabling robust versioning and collaboration capabilities. Multiple team members can work on the same LookML model simultaneously, track changes, and easily roll back to previous versions if needed. This promotes collaboration, helping to maintain data accuracy and consistency across the organization.
While comparing Looker vs Tableau from a dashboard or visualization perspective, Looker makes it easy to connect your data to Google Workspace tools like Slides and Sheets. Meanwhile, Tableau also offers quick dashboard integration for applications in Salesforce and Sharepoint. But when it comes to git integration, the process in Tableau is clunky and cumbersome.
Looker's pricing has a complex structure of multiple components that may leave you uncertain about your costs. The two main components are platform pricing and user licensing. The platform pricing for standard, enterprise, and embedded—which covers instance operation, administration, integrations, and semantic modeling capabilities—lacks specific details on what those integrations entail and how they could impact your expenses.
When it comes to user licensing, Looker offers three types: Developer User, Standard User, and Viewer User. The varying user privileges and their associated costs might make it difficult to determine which license type suits your users best.
Furthermore, Looker's user licensing fees, ranging from $30 to $125 per user per month, could add up quickly, especially for organizations with a large user base.
As far as Tableau pricing is concerned, Tableau license types include Tableau Creator ($75 per user/month), Tableau Explorer ($42 per user/month), and Tableau Viewer ($15 per user/month). Understanding which license type is suitable for your users can be a complex and potentially confusing process. There are several aspects of Tableau’s pricing structure that may raise concerns about the total cost of ownership and whether it aligns with your organization's needs.
Beyond the base license fees, there are other factors that can impact the total cost of ownership. If you choose Tableau Server, there are additional costs for hardware, maintenance, and support, which might not be immediately evident.
The recent wave of AI and innovation are pushing companies to be more agile. As you scale your data operations, you should prioritize a powerful and intuitive alternative to Tableau and Looker—one designed to help consumers at every skill level find value in your data.
ThoughtSpot’s AI-Powered Analytics offers just as broad a range of data connection sources and analytics features as either of the competitors listed above, but it ranks highest on self-service analytics. Even better, ThoughtSpot Sage, which pairs the ease and flexibility of LLMs with robust accuracy, security and governance, is actually live. Our customers are already using it to transform how their teams get insights and make decisions. Our natural language queries and search-based interface empowers users to ask data questions and find trusted insights, and drill anywhere into their visualizations to find the insights they need to make important decisions—in seconds, not weeks.
ThoughtSpot’s transparent pricing puts you in control of your data spend. The most robust Enterprise plan comes with all the bells and whistles at consumption-based cost. Plus, there's a Team Edition for small organizations that starts at $95/month.
The best data solutions help you align your data strategy and your business strategy to deliver true value. That’s why customers like Comcast, Mattel, and CVS trust ThoughtSpot to provide self-service, AI-Powered Analytics. But don’t just take our word for it—get a demo and see the value that a modern data experience delivers for your business.
Just as data is constantly evolving, so are Google and Salesforce—by the time you read this, specific offers may have changed. It’s always best to confirm specs with the source.