Looker versus Looker Studio: What are the differences?

1 February 2024 | 3 minutes of reading time

• We often see this question come up. But we also notice that people sometimes confuse the two Lookers. There seems to be some confusion between the 'big' Looker and the 'small' Looker Studio. Understandable, since both are reporting solutions and they also share almost the same name. However, there are significant differences, and through this article, we aim to clarify the differences and similarities between the two.

What is Looker?

Advantages:

• Extensive data modelling via LookML, the proprietary 'semantic layer'.
• User-friendly interface with extensive data exploration and visualization options, for self-service BI.
• Numerous options for self-service BI.
• Many options for collaboration and sharing information. For example, you can schedule reports to receive them daily, weekly, or monthly in your mailbox.
• Version control of code through Git.
• Good governance capabilities such as access rights for (groups of) users, audit trails, and specific users can log in to investigate any issues.

Disadvantages:

• A significant learning curve for analysts who want to work with LookML, in contrast to the user-friendliness for end-users.
• Looker requires a higher investment than most visualization tools.
• Looker can only process structured data from databases. It cannot directly process data from APIs or other sources than a database.

What is Looker Studio?

Advantages:

• Looker Studio is free to use, making it attractive for organizations with fewer requirements for governance or advanced analyses.
• Good integration with Google products such as Sheets, Analytics, Bigquery, and Ads.
• Easy to use for both analysts and end-users.
• Collaboration and sharing of dashboards are easy to achieve, just like with other Google products.

• Less suitable for large, complex datasets due to limited data processing capacity.
• Being a free tool, it has its limitations, such as in analysis capabilities.
• No version control, governance capabilities, and fewer advanced collaboration options.

The differences at a glance

Looker:

• Developed to assist businesses with advanced data analysis through a semantic layer (LookML).
• Offers extensive capabilities for data modeling, integration with various data sources, and advanced visualization options.
• Aimed at both regular users and data analysts, with possibilities for self-service BI.
• Provides functionalities for collaboration, version control via Git, and good governance options.
• Its disadvantages include the complexity of LookML, higher costs, limitation to structured data from databases, and potential performance issues with large datasets.

Looker Studio (formerly Google Data Studio):

• A free data visualization and business intelligence tool developed by Google.
• Can connect to over 800 different data sources via a library of partner connectors.
• Easy to use, with good integration with other Google products and easy collaboration options.
• Less suitable for large, complex datasets due to limited data processing capacity.
• Lacks advanced capabilities such as version control, governance, and has limited analysis capabilities compared to Looker.

Our advice?

Need more advice?