5 Best Looker alternatives
Last updated on
January 5, 2023
Truly data-driven companies don’t just rely on their engineers or data analysts. They know that every single team member must be able to quickly, easily, and intuitively engage with the data they need for to make better business decisions.
Looker is one popular choice for companies looking to make data accessible across their entire workforce. It offers business intelligence to non-technical users through highly attractive data visualisations and customisable queries that let your team dive deep into the data.
But it’s not the right choice for every company – it’s really meant for larger-scale deployment and it uses its own proprietary language, which means your team will still rely on engineers or data analysts for setup and troubleshooting.
In this article, we've compared 5 of the top alternatives to Looker that can help you truly empower your business users.
5 Best Looker alternatives for 2023
Here’s our pick for the 5 best Looker alternatives to give your team data super powers:
An overview of Looker
Looker is one of the leading business intelligence tools. Founded in 2012, it was later acquired by Google in 2019. It now forms a part of Google Cloud and also powers part of Google's Data Studio platform.
- Attractive data visualisations including interactive dashboards that give your team an overview but also let them go deeper on metrics.
- Flexible customisation options, with a centralised DSL (domain-specific language) modelling layer designed to tailor data analytics to your needs.
- Sophisticated data modelling capacities for enterprise-scale deployment.
- Easily joins multiple data sources.
- It’s one of the more expensive BI tools.
- There’s a steep learning curve since Looker uses its own modelling language, LookML, rather than SQL, which can disempower business users.
- You’ll have to rely on your IT team to set up and generate datasets as well as perform maintenance and troubleshooting.
- There’s a heavy focus on complex data modelling features, targeted at data experts, and less of a focus on intuitive data exploration for business users.
How much does Looker cost?
Quotes vary according to the number of users and data you’ll use – Looker doesn’t publicly release their pricing information. Typically, it’s estimated at around $3,000-$5,000 for 10 users, though, which makes it an expensive tool.
Which companies use Looker?
Larger or enterprise-scale organisations with a sizable data budget and a data team who can manage their BI tool.
Top 5 Looker alternatives
So who are Looker’s competitors? Our top 5 Looker alternatives provide data visualisation and exploration for business intelligence but also offer lower price points, less of a learning curve, and more accessibility for your non-tech team.
The best and fastest-to-implement data platform to empower your whole team.
Trevor.io is an all-in-one self-service data analytics tool that empowers non-tech users to explore data and find answers to their business questions.
- No-code queries in just a few clicks gives non-techies a powerful, intuitive way to engage with data.
- Super-versatile – you can build any kind of dashboard you want, and business users can easily run ad-hoc queries on the fly to get immediate visibility on metrics and take actions based on user or customer data.
- Deep data exploration, with customisable drill-down functionality.
- Rapid setup: Trevor.io automatically detects joins in databases across multiple data sources and you don’t have to go through any extra steps like modelling your data first.
- Integrations with APIs mean you can automate a huge number of actions, which empowers your team to streamline their workflow and keeps everyone in the loop with data alert features on Gmail, Salesforce, Slack, Xero. It even includes an Excel auto-update feature.
- Accessible pricing plans that are all-inclusive with unlimited users and no hidden costs.
- Protects your database from too much load with automatic limits to in-platform rows and active connections to speed up functionality.
- Live chat support with speedy reply times.
- It currently has a limited range of features for embedding data directly into other applications – but a greater range of features is coming soon. Trevor.io has a policy of continuous development and the team launch new features all the time.
Is Looker better than Trevor.io?
Here’s how the tools stack up:
- Data analytics: Trevor.io has better drill-down features and agile ad-hoc data exploration capacities while Looker has more emphasis on data modelling.
- Accessibility: Looker has a higher learning curve and requires more tech maintenance than Trevor.io.
- Support: Both tools offer excellent customer support with quick response times.
- Pricing: Looker is more expensive than Trevor.io.
If you’re considering Looker, take a look at our breakdown of customer-hosted Looker alternatives.
Data-hungry companies that want to truly empower their non-tech team to run complex, ad hoc queries and drill down on data. Especially recommended for growing SaaS and marketplace companies looking for a customisable tool that offers business intelligence as they grow and scale.
The best for companies looking for embeddable analytics.
Sisense is a Looker competitor with an agile analytics platform for data exploration and visualisation.
- Intuitive and agile data analytics for non-tech users.
- Innovative AI machine learning functionality that automatically draws attention to key insights.
- Analytics and visualisations that can be easily embedded into workflows, applications and reports.
- Scalable functionality with a columnar database approach that allows it to handle big data and join multiple data sources.
- Sisense Elasticube technology requires SQL to set up and often needs troubleshooting, which slows down non-tech users.
- Heavy application that uses a lot of server power and space.
Like Looker, Sisense doesn’t release its pricing – they custom build quotes based on the number of users and data size. Reviews suggest that plans typically start at $17,000 per year.
Is Looker better than Sisense?
Here’s how Looker and Sisense compare:
- Data analytics: Sisense offers more agile data exploration including ad-hoc queries while Looker has a more rigid data model.
- Accessibility: Sisense is more accessible to business users than Looker, and requires fewer tech resources to leverage its analytics.
- Support: Both tools offer well-rated customer support.
- Pricing: Both tools are expensive, high-end options.
Larger, established companies who prioritise agility and versatility in data exploration, and who have engineering and data resources with time to set up and troubleshoot the technology.
The best for basic no-code queries.
Metabase is an open-source tool with drag-and-drop features for ease of use. Here’s a breakdown:
- Intuitive, no-code BI tool that allows business users to get answers to their questions.
- Comprehensive visual analytics for data exploration.
- Data alert automations and integrations with several apps.
- The drag-and-drop tool doesn’t allow for much granularity or ad-hoc data queries.
- SQL knowledge is needed to run sophisticated queries and variables, which limits the non-tech team.
- Setup can be tricky, with a limited capability to join data from multiple SQL data sources.
Is Looker better than Metabase?
- Data analytics: Looker offers more complex, granular data exploration through its no-code tool than Metabase, but neither tool is especially versatile for ad-hoc queries by ordinary business users.
- Accessibility: Both tools require some tech support from your data team – they’re not fully accessible to business users.
- Support: Lookers offers better customer support than Metabase.
- Pricing: Looker is more expensive than Metabase.
If you’re considering Metabase, take a look at our deepdive into Looker vs Metabase, as well as a breakdown of top Metabase alternatives.
Companies looking for more basic Looker alternatives, whose business users don’t need to run ad hoc queries or find granular data.
The best for companies looking to create complex data visualisations.
A popular Looker alternative, Tableau is a Salesforce-powered business intelligence tool that uses its own in-memory data store.
Here’s what stands out:
- No-code, natural language queries.
- Data visualisations are intuitive and easy to interact with, which lets your whole team explore data.
- Integrates into the entire data workflow, with features for data governance as well as data analysis.
- It has a high learning curve, and business users will need support from your engineers for setup, data management and troubleshooting of the in-memory data store.
- You’ll need to invest in data cleaning before using it.
RELATED POST: 6 Tableau Alternatives to Help You Visualise and Analyse Your Data
Is Looker better than Tableau?
- Data analytics: Both tools offer impressive data analytics and visualisations, but Looker may allow users to go even deeper into the data (though only by using SQL).
- Accessibility: Both tools have a significant learning curve and non-techies will need support from your engineers or data team.
- Support: Both tools offer decent customer support.
- Pricing: Looker is typically more expensive than Tableau – but if you’re a growing company with increasing user numbers, Tableau can also get pricey.
Who is Tableau best for?
Enterprise-scale companies looking for a tool for data governance and data analysis, that have a dedicated data team to extract the most value from the tool.
RELATED POST: Looker vs. Tableau vs. Trevor: Which Tool is Best For You?
The best dashboarding tool for SQL experts.
Redash is one of the top open-source Looker alternatives, with an SQL-based business intelligence platform that allows for a range of data analytics and visualisations.
Here’s what you need to know:
- Quick connection to data sources.
- Drag-and-drop data visualisation layer.
- Data analytics are easily shareable through integrations with several third-party apps.
- Data can be auto-updated so your team stays on top of any changes.
- The open-source version is free to use if you run it on your own servers.
- There’s no direct customer support available for the open source software – you have to rely on a help forum.
You need SQL expertise to use it, so it’s not a self-service BI tool designed to empower non-tech users.
Open source is free – here’s an overview of their paid plans:
Is Looker better than Redash?
Here’s how they stack up:
- Data analytics: Looker offers more advanced data analytics, visualisation, and customisation options than Redash.
- Accessibility: Though it also requires support from your data team, Looker is more targeted to non-tech users than Redash, since Redash requires SQL expertise.
- Support: Looker offers more extensive customer support than Redash.
- Pricing: Looker is significantly more expensive than Redash.
Who is Redash best for?
Smaller companies or startups who want something super low-cost, are willing to deploy tech people for data analytics and don’t need data to be accessible to the rest of the team.
Didn't find the right tool in the list above?
The business intelligence software space is large and there are a plethora of tools, whether you're looking for real-time insights, or the ability to do forecasting, or embedded analytics for your customers, or any number of other relevant use-cases.
Here are some other cloud-based or on-premises business analytics solutions to check out:
- Microsoft Power BI - a great option if you're part of the Microsoft ecosystem.
- Sisense - a great option for embedded analytics.
- Qlik - a feature-rich cloud platform, great for visualizations.
- Zoho Analytics - a BI platform used by some large enterprises.
- Domo - a great option to build data apps.
What’s the best alternative to Looker?
While all business intelligence platforms are designed to make data more accessible, only some will really give your business team data superpowers.
It’s important to take time to explore the different Looker alternatives and find the perfect match for your company. Trevor.io is a great choice for agile, ad-hoc data exploration that will really empower your business team to become data-driven by getting their hands dirty and answering all their own data questions.