Why Omni over Looker?
Free your data team from being a bottleneck with a flexible shared data model, a fast and modern platform, and exceptional customer support.
Self-service for everyone: Explore data using a point/click UI, Excel calculations, SQL, or AI – no specialized knowledge or skills required.
Flexible data modeling: Model data as you go, without having to model data upfront.
First-class customer experience: Get fast product development, white-glove support, and a modern, user-friendly UI.
Bi-directional dbt integration: Push Omni metrics to dbt, test dbt model changes before you ship them, and more – helping you move faster with dbt than in Looker.
Faster load times: Reach answers quicker through Omni’s intelligent caching, without added costs.
Using Omni has reduced the number of new questions and consolidated the reports our Analytics team needs to build. It’s given us time back while giving our stakeholders more independence to explore what they need.- Lizzy Bradford, Senior Director of Analytics
Migrated their eight-year-old Looker estate and launched company-wide in less than three months
Read case studyHow Omni & Looker compare
Customer experience is core to how Omni operates.
Omni launches new features weekly, provides white-glove chat support to all customers, and has a user-friendly, customizable interface. Looker product development has slowed down and customer support has degraded since being acquired, while the product has remained rigid and inflexible.
Our Engineering team ships product updates fast. We develop in the open for everyone to follow along at omni.co/demos
Looker’s product development has slowed down. Customers note that Looker has become increasingly complex and lacks meaningful improvements on the roadmap.
Their support and sales teams are fantastic and I am also quite taken aback by their ability to deliver new features and functionality at a rapid pace.
– Omni customerOver time, [Looker] became overly complex and performance degraded. It was also missing features we needed with no sight of them on the roadmap.
– Shyam Sivakumar, Head of Data at Ascend (read the case study)White-glove Slack support is included for all customers, so you can get help solving problems in real-time, not days later.
Support isn't a priority and has degraded in recent years. Google replaced the support team with offshore contractors after acquiring Looker.
We just love the shared Slack channel for customer support. It feels really encouraging and collaborative, even when the answer is ‘We can’t do that yet, but here’s a workaround.’ We use a lot of platforms, but this level of support is unique to Omni.
– Luke Ruth, Chief Product Officer at Fundrise (read the case study)The support team is close to nonexistent and there aren't many support resources that explain how to do complex tasks with it.
– Looker customerOmni’s UI is modern, user-friendly, and easy to customize. Whether you’re building for internal stakeholders or your customers, use custom visualizations, Markdown, and CSS dashboard controls to help you make Omni feel just right for your organization.
Looker’s UI has been outdated for years and often requires time-intensive coding to customize.
Omni’s customization options allowed us to make our embedded analytics match our brand and give our customers a more cohesive experience.
– Chris Snyder, Director of Data Science at ActiveProspect (read the case study)It is harder to use compared to other BI tools, and you need someone that's expert in Looker to do a lot of the advanced functions.
The visualization and layout of the reports are also not the best.
– Looker customerWith Omni, you don't have to compromise on speed or data freshness.
Looker's simple caching means data is often pulled directly from the database, resulting in long dashboard load times. Omni’s intelligent cache ensures you’re getting fresh data without the wait.
Omni's intelligent cache combines the speed of extracts and the data freshness of direct queries without added costs. This happens out of the box — no additional configuration required.
Looker's simple default caching results in long load times as the database often gets queried directly. Any improvements require extensive manual configuration.
Some reports and dashboards, especially the ones used by GTM, used to take 20 to 30 seconds to load with Looker. With Omni, it loads in less than half the time.
– Shyam Sivakumar, Head of Data at Ascend (read the case study)It is extremely slow to load and work with. It's like pulling teeth to work in bulk on things.
– Looker customerSlow load times in Looker are the second most common complaint on G2, an independent review site
Omni saves time for the data team by streamlining data engineering workflows.
Maintaining your data stack with Looker is tedious. Omni makes it easy to keep everything in sync.
Omni's layered data model gives you flexibility. Promote reusable metrics to the shared model while keeping ad-hoc metrics in workbooks to prevent model bloat.
Looker's data model becomes hard to maintain over time. Every metric and data cut needs to be modeled centrally by the data team.
It's super easy to create your own metrics or derive metrics from existing ones and start building super powerful insights quickly. If what I build's good, we just promote the new metrics into the model so they can be reused everywhere by all users.
– Omni customerLooker originally made it much easier to model data than previous tools, but over time, the tool became overly complex and performance degraded.
– Shyam Sivakumar, Head of Data at Ascend (read the case study)Push new metric definitions and model changes to dbt via a bi-directional integration to make them universally accessible and optimize performance.
Looker creates a data silo. Metrics developed in Looker's data model cannot easily be pushed to dbt, making them inaccessible for other use cases and tools.
Safely test the impact of changes to underlying data sources. Use Omni's dynamic schemas to switch between dev & prod environments and update your content in bulk with the content validator.
There's no easy way to safely test schema changes. Any changes to underlying data sources need to be manually reflected in every single query in Looker to prevent content from breaking.
One of Omni's best features is the ease of updating your schema whenever it changes. In other BI tools, this requires several steps in several places that are multiplied by the number of schema changes; with Omni you just click refresh.
– Omni customerOmni provides self-serve analytics for everyone — without a steep learning curve.
In Looker, the data team has to build everything using LookML before business users can analyze data. Omni lets users get started quickly and contribute to the data model as they go.
Anyone can explore, analyze, and visualize data with Omni. Users can query with a point/click UI, Excel formulas, SQL, and AI, regardless of their data proficiency.
Looker has a steep learning curve. It's difficult for less technical users to get the answers they need without help from the data team since ad-hoc analysis is limited.
[T]here have been very specific analytics tools that cater to a governed model, iterative SQL analysis, or workbook BI. Omni supports all of these workflows simultaneously, which unlocks all departments within an organization to be empowered as data analysts.
– Omni customer[W]e've struggled to get non-data people into the tool to really use it as they find it hard to use without significant training.
– Looker customerGet insights without waiting for the data team. You can build your data model directly from the intuitive UI and create new metrics as you do analysis, giving you the best of both worlds: governance and speed.
Your data team is a bottleneck, even for small changes. Metrics need to be modeled before doing any analysis, which requires your data team to use Looker's proprietary language.
I love having the ability to edit the SQL directly and then just promote it to the shared model so the entire organization can use it. What used to take 15 minutes [in Looker] is just five clicks for me now, Omni saves me a lot of time.
– Shyam Sivakumar, Head of Data at Ascend (read the case study)With Looker, I knew our data team would always be a bottleneck.
– Jade Khiev, Insights Engineering Lead at Rose Rocket (read the case study)By switching to Omni, Rose Rocket was able to reduce the number of questions the data team gets by 80%.
Upload CSVs, enter new values, and write data back to your warehouse. Anyone (with the right permissions) can use Omni's data input to bring in data from anywhere and analyze it immediately.
The data team has to upload any ad-hoc data into your database to analyze. Looker doesn't allow CSV uploads (CSVs can only be uploaded in Looker Studio, which is a separate product). There's no way to directly edit data or write it down to your warehouse.
A lot of our non-technical users are able to upload data that doesn't live in our data warehouse; it's fantastic because they don't need engineering resources to do their work.
– Setareh Lotfi, CTO @ Aura (read about their use case)Even though Looker has useful resources, I miss the possibility of using the tool to analyse any database of any source, even csv or xlsx files.
– Looker customerIf you like dbt, you'll love Omni's dbt integration
Omni's dbt integration is robust and supports real analyst workflows: switching between dev & prod schemas, creating dbt models from logic in your BI platform, and more.
Looker doesn't have a built-in dbt integration. You can query dbt models from your database, but it doesn’t go deeper than that.
See how Omni's dbt integration compares to Looker's
Compared to Tableau and Looker, Omni was by far the best performer in terms of all-around functionality.— Cody Pulliam, Senior Manager of Business Analytics
Customer love
"Omni Analytics is a sweet spot between Looker and Mode. It's easy for your team to use, like Looker, but also lets tech-savvy folks dig into data with SQL queries. Plus, the Omni team is super quick to support and brainstorm on new ideas."
Read full review"I am not a BI tool user nor a data engineer but am able to model data and create dashboards much easier than other tools we tried. The tool is fast and responsive. The team is helpful and supportive and if you want get under the hood it's very easy to do so"
Read full reviewA super powerful BI tool. Omni addresses many of the struggles in legacy BI tools with novel approaches. The team has built with the analyst in mind so well. With Omni, data engineering can end a step or two earlier and rest of the magic is taken care of by the Omni UI. I also love how quickly Omni iterates and launches new features. Customer support of the finest levels too."
Read full reviewFAQs
Omni is a relatively new tool. Does it have the same features as Looker?
Looker offers a comprehensive set of features for companies wanting a BI tool with a governed data model.
However, Looker is complex to use and difficult to maintain, making the Data team a bottleneck for business users looking for insights.
In contrast, Omni's flexible architecture unlocks the governance of a data model while reducing the burden on the Data team. In Omni, users can build the data model directly in the UI and evolve it iteratively as they do analysis. In addition, Omni's intelligent cache results in faster dashboard load times, addressing one of the key pain points teams have with Looker.
I like the control that Looker's governed data model provides, and I'm worried I'll lose that with Omni.
Looker gives data teams a lot of control in building and governing their data model. Unfortunately, this comes at a cost: Users need to learn a new language, LookML, to take advantage of these features.
Omni gives you the same level of control, but with more flexibility. If you want to build your data model in advance, you can. Or, you can create and define metrics as you analyze, using the workbook UI to speed you up. For any metrics that should be accessible across the company, you can promote fields to the shared data model.
Omni's architecture also streamlines your data engineering workflows. For example, any changes you make in dbt will automatically be reflected in Omni's schema layer with a single click. In Looker, you need to update your LookML manually to reflect upstream changes.
Why do I need a semantic layer in Omni if I'm using dbt? Business logic shouldn't sit in the BI layer.
While in theory you could have all business logic confined to dbt, in practice this creates bottlenecks.
To keep up with the pace of business, users constantly need new measures or dimensions. With Omni, your teams are empowered to explore the data and get the answers they need. If any of these ad-hoc metrics should be part of the permanent data model and used by the broader organization, you can push them to Omni's shared model or to dbt to close the loop.
Omni's semantic layer also creates a foundation for AI to deliver trustworthy responses. You can leverage descriptions, AI-specific context, and other metadata from your semantic model to inform AI answers.
We want to enable self-serve analytics for our business users. Which tool should I choose?
Both Omni and Looker are designed to provide self-serve access to data while maintaining metrics consistency through a governed data model.
In practice, though, Looker's steep learning curve and rigid data model mean that business users cannot independently do ad-hoc analysis and generate insights. The Data team needs to model all metrics in advance in LookML, which becomes a bottleneck even for small changes. Custom fields and table calculations are not sustainable workarounds because they only exist in a single query and cannot be reused across a dashboard or shared with others.
In Omni, on the other hand, users are free to explore data in a way that works best for them (point/click UI, Excel calculations, SQL, or AI), and metrics developed in workbooks can be promoted to the shared data model to be centralized and reused across the company. You can even push the new metrics down to dbt to make them accessible by other tools and improve performance.
A good example is Omni's period-over-period analysis feature, which lets users easily compare data across time periods with the UI - no technical skills required. Looker only built this feature in 2025 after years of feature requests from customers, and it still has to be defined in LookML by the data team before business users can benefit from it.
Many of our BI users don't know how to write SQL. Which tool is a better fit for our situation?
Both Looker and Omni let you explore data and create visualizations in a UI without using SQL
Omni also lets you manage your data model directly from the UI, but in Looker, you have to program it in a proprietary language (LookML). That means business users can only use fields created by the data team in advance, severely restricting their ability to explore data and generate insights independently.
Using SQL or another coding language is not required in Omni - we give every user the option to work in the way that they prefer. When exploring data or building dashboards, you can seamlessly switch between the point/click UI, Excel calculations, AI, and SQL. In the background, Omni is translating all queries into SQL, so you can always switch to SQL mode if you prefer.
We have a small data team with limited bandwidth. Which tool is a better fit for us?
Both Looker and Omni allow for self-service data access for business users, which is great for busy data teams.
However, since data modeling in Looker requires specialized knowledge, business users rely heavily on the data team, even for small requests. In Omni, users can contribute to the data model directly in the UI, allowing them to independently explore and analyze data and freeing up the data team's time to focus on higher-impact tasks.
In addition, Omni's data model is easier to maintain and keep in sync with your database. For example, in Looker, any changes to underlying data sources (e.g. changing a field name in dbt) need to be manually updated in LookML. In Omni, you can refresh the schema and update references with a single click.