Beyond Looker Studio and Looker: A Comparison of Modern BI Tools for Growing Businesses

Recently, we assisted an organization in evaluating their options in the BI vendor space. The organization had been utilizing Looker Studio (aka Google Data Studio), a freemium BI tool that's a solid starting point for companies just beginning to expand their analytics practice, especially if they're already using Google's suite of data products like GA4 and BigQuery. However, Looker Studio has its shortcomings, particularly regarding administrative capabilities. While you can upgrade to an enterprise license or build a front-end wrapper to manage access to visualization assets, these solutions are not only limited but also incur additional costs. Our goal was to identify a scalable solution that could support growing internal BI adoption and simultaneously provide a platform for an emerging embedded customer-facing data product. In this pursuit, we looked beyond Looker Studio to its namesake, Looker—though I must take a moment to ruefully acknowledge Google's perplexing branding choices (yes, that's sarcasm).

Looker's pricing for the necessary combination of internal and external licenses amounted to a hefty six-figure annual sum. However, the cost was just the tip of the iceberg of reasons to search for alternatives. Here are the primary reasons why Looker has fallen out of favor for most BI use cases:

• Looker is akin to a well-preserved dinosaur, a once-promising BI tool that, post-acquisition by Google, seems stuck in its late-2010 prime. Updates to meet modern data needs have been noticeably lacking.
• Looker's reluctance to develop new chart visualizations has left a gap filled by the JavaScript community, leading to a subpar offering compared to the Tableau standard.
  
• The integration between dbt and Looker has always been clunky, with redundant configurations necessary across both platforms that should be streamlined into one cohesive workflow.
  
• Sticking to user-based license pricing, Looker has not caught up to the consumption-based pricing many customers now prefer for more predictable budgeting.
  
• Though Looker integrates with git, it falls short in providing a full DevOps suite. This is evidenced by third-party startups creating solutions like Spectacles to address the deficiencies.
  

Where then do we turn if not to Looker? We guided our client through the evaluation of two innovative BI solutions: Omni and Lightdash.

Omni

In the past year, Omni has made impressive strides, utilizing the expertise of its Looker-experienced team to expand upon Looker's foundational features. Our client's pilot program revealed Omni's adeptness at bridging BI tools and spreadsheet functionalities, which is crucial for data-intensive businesses. However, Omni's relative neglect of a robust GitHub-based CI/CD framework—a significant need for the client planning a sizeable embedded rollout—was a sticking point. Omni's philosophy encourages developers to remain within its ecosystem for virtually all development stages, but this doesn't cater well to scenarios requiring developed templates for scaled reporting, where integration with GitHub and DevOps actions is crucial.

To summarize Omni's fit within our criteria:

• Price: User-based pricing remains, which might lack transparency for companies unsure about user growth, yet it is more amenable for SMBs.
• Development Speed: Omni maintains a fast-paced release cycle, frequently introducing new features.
  
• Custom Charts: While Omni uses Vega-Lite for custom charts, it does so within its system, unlike Looker, which depends on external solutions.
  
• Git/DevOps: Currently, Omni lacks git integration and has limited DevOps capabilities outside its proprietary revision history features.
  

Lightdash

Lightdash, a newer and promising BI tool, aspires to evolve beyond Looker. While it still has some catching up to do, particularly with features that Omni has mastered, Lightdash presents a more affordable and intuitive iteration of Looker's essentials. Its synergy with dbt is notable, allowing for smoother metadata configurations and an integrated development experience that is both developer and consumer-friendly. With a git integration already in place, Lightdash sets up a clear path for implementing GitHub Actions-based DevOps workflows.

Assessing Lightdash according to our established criteria yields:

• Price: Lightdash not only offers an open-source, self-hosted solution but its cloud version comes with unlimited users. Their consumption-based pricing for embedded dashboards presents a flexible option poised to fit diverse user scenarios.
• Development Speed: Public visibility of their development on GitHub and a Slack community keep users updated on feature releases and planned milestones.
  
• Custom Charts: Lightdash also utilizes Vega-Lite, offering in-app customization for charts.
  
• Git/DevOps: Lightdash excels in this area, providing solid routes for implementing GitHub Actions, supporting everything from code validation to content promotion between development and production environments.
  

In the fast-evolving world of BI tools, decision-makers must consider not only current needs but also anticipate potential growth and future demands. Both Omni and Lightdash offer promising features and value propositions, but the question of which tool best aligns with your strategic direction requires careful deliberation. Lightdash, with its community-driven innovation and flexible pricing, may be particularly appealing for organizations looking to scale rapidly without being tied down by license constraints. As the BI landscape continues to shift, identifying a tool that will grow alongside your business is paramount. If you're interested in how we might help you with a similar solution, feel free to schedule an intro call here.

Note: The criteria comparison above does not capture all criteria we considered, rather, we are calling out the criteria where Looker Studio and/or Looker fall short. The full list of criteria in our BI tool evaluation process: functionality, integrations, scalability, ease of use, customization, mobile accessibility, security/row-level, cost, support and training, vendor reputation, deployment options, performance, reporting flexibility, collaboration features, development workflow.

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