Whaly's self-service BI platform is an alternative to Looker. Here's what we've gathered around the pros and cons of both, to help you evaluate the BI tools on the market.
Looker claims to be a business intelligence solution that drives better outcomes through smarter data-driven experiences. Their purpose is to enable organizations to equip their employees, customers, operational workflows, products, and services with timely and trusted data. Originally designed for data engineers, Looker has expanded to focus on self-service capabilities for business users. Looker launched in 2012, and was acquired by Google in 2019.
Whaly is an integrated, self-service business intelligence platform that enables business teams and data teams to work better together - streamlining the path from data to decisions. Our mission is to grow data adoption and company-wide trust in data by empowering business teams to access and analyze data, whenever and however they need it. Whaly includes data connection, modeling, and visualization all in one. Our robust modeling layer is also user-friendly enough for data-savvy business users to participate.
A good self-service BI tool should always enable clear, ongoing visibility into data at all times, and should be accessible and beneficial to everyone. These factors are vital for business teams to make informed, timely decisions. As such, things like learning curve, lengthy training time, implementation time, slow performance and load time, and limitations for non-technical business users are red flags.
While Looker is a robust, powerful BI solution that equally plays in the self-service analytics space, there are certain downsides that negatively impact the ongoing accessibility of data for all users. In this comparison, we’re considering the perspective of a SMB / mid-market company that’s less mature in their data journey, with a small data team. The main downsides include LookML proprietary language requirements, slowness, overall learning curve and complexity, and cost.
Whaly, on the other hand, is fast to implement, learn, and load, uses raw SQL with no specific requirements. Plus, we’re significantly cheaper with free viewer licenses.
|Pricing||Per user, pay for viewers.|
Enterprise plan ranges from 40K to 100K per year.
Training and implementation are paid (20k).
|Mix of usage-based and user-based; viewers are always free.|
Cloud options start at $460/month.
Implementation is included, along with 1 training session.
|Learning curve||Steep - must learn proprietary language (LookML). Heavy coding requirements in modeling, exploration, and iteration.||Easy - all SQL-based with visual builder option. Easily accessible for business users with no technical expertise.|
|Average roll-out time||6 to 18 months. Takes longer including time to learn LookML.||1 to 3 weeks|
|Data connectors (ETL)||Not included||Included|
|Integrations||No integration with dbt, which means work will be duplicate in dbt and LookML.|
Connected with limited sources. GCP ecosystem is seamless.
|Native integration with dbt.|
Connects with 150+ sources.
|Speed||Load time could take up to several minutes due to heavy processing power||Fastest speed/performance on the market built on latest technology|
|Interface||In-browser; no desktop install. Mobile version is limited.||In-browser; no desktop install|
|Software updates||Updates are completed per customer and not globally for all customers, which can be a pain when migrating your deployment.||Whaly updates all customer deployments at all times and makes sure nothing is broken and no one is left behind.|
|User permission management||Yes||Yes|
|Self-service||Yes, for consumption. Very limited self-service capabilities for configuration, with LookML requirements.||Self-service for modeling (data-savvy), exploration, and consumption. Configuration requires a main builder with SQL knowledge.|
|Modeling layer||Code required in modeling, in proprietary language (LookML)||SQL-based or visual builder. No proprietary language to learn. Drag & drop is available for non-technical users.|
|Visualization for business teams||Comprehensive capabilities. You can also develop your own visualization if needed||Comprehensive capabilities and customization|
|Row limits||Limit at 5,000 rows for results; makes it difficult to scale||Limited to 50,000 rows|
|Export / Share / Embed||Must enable public access of Looks to be able to share externally (no password protection).|
Looker allows you to share your data, but it’s paid.
Strong Embedding API.
|Whaly’s “push” feature allows reporting to be pushed out to your preferred channels (Slack, Email). Dashboards can be embedded into wherever you already work (HubSpot, etc).|
With Whaly, it’s free to share data out.
|Customer support||No more US CS team in place. Expect long delays in terms of responsiveness and resolution||Highly reactive with SLAs in place; quick problem-solving|
In summary, Whaly offers a self-service BI platform with the same robust and powerful capabilities as Looker, but at a fraction of the cost. Plus, we offer a lighter, faster, and more flexible platform that scales with fast-growing companies like you, enabling ongoing collaboration and trust between data teams and business teams. Our SQL-based modeling layer also makes us more accessible and truly self-service at every level. Lastly, you need data-driven insights today, so why wait 18 months?