Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.
$6.25
per TiB (after the 1st 1 TiB per month, which is free)
Looker
Score 8.3 out of 10
N/A
Looker is a BI application with an analytics-oriented application server that sits on top of relational data stores. It includes an end-user interface for exploring data, a reusable development paradigm for data discovery, and an API for supporting data in other systems.
N/A
Microsoft Power BI
Score 8.5 out of 10
N/A
Microsoft Power BI is a visualization and data discovery tool from Microsoft. It allows users to convert data into visuals and graphics, visually explore and analyze data, collaborate on interactive dashboards and reports, and scale across their organization with built-in governance and security.
$168
per year per user
Pricing
Google BigQuery
Looker
Microsoft Power BI
Editions & Modules
Standard edition
$0.04 / slot hour
Enterprise edition
$0.06 / slot hour
Enterprise Plus edition
$0.10 / slot hour
No answers on this topic
Power BI Pro
$14
per month (billed annually) per user
Power BI Premium
$24
per month (billed annually) per user
Offerings
Pricing Offerings
Google BigQuery
Looker
Microsoft Power BI
Free Trial
Yes
Yes
Yes
Free/Freemium Version
Yes
No
Yes
Premium Consulting/Integration Services
No
Yes
No
Entry-level Setup Fee
No setup fee
Required
No setup fee
Additional Details
—
Must contact sales team for pricing.
Power BI Desktop is the data exploration and report authoring experience for Power BI, and is available as a free download.
I personally find it by far simpler than Amazon Redshift due it's onboarding seamlessness. For a quick start and simplify tye access to read the data big query provide better user experience and a smoother user interface. More importantly, the fact that Big Query can be easily …
It's easier to connect data between BigQuery and Looker Studio instead of connecting the data between BigQuery and Tableau in terms of data explore or dashboard creating. Therefore we are considering migrating dashboards from Tableau to Looker Studio for the whole company. On …
Google BigQuery seemlessly integrates with all the Google services. In Looker Studio you directly have a connector for Google BigQuery which can help to create dashboards in few clicks. For automating some stored procedures we have used Cloud Functions which are triggered by a …
Google BigQuery of course collects a much much larger array of raw data and can handle (practically) an unlimited amount of data. For a large enterprise like ours that relies on large-scale analytics, this is absolutely imperative. Google BigQuery can also combine GA4 data with …
PowerBI can connect to GA4 for example but the data processing is more complicated and it takes longer to create dashboards. Azure is great once the data import has been configured but it's not an easy task for small businesses as it is with BigQuery.
Main reason is how it integrates directly with the google ecosystem which really facilitates the automatization proceses for the whole company. This ensures that sales and all the other departments have the correct information on a daily bases with a ease of use with day to day …
I have used most of the data analytics platforms. Based on my work, I have found that the user interface of Google BigQuery is simple to navigate. I like the front view - ease of joining tables, and integration with other platforms.
In my opinion, Google BigQuery is custom made to be the best data lake system that is easy to use, scalas to fit any business size, has inbuilt security, as well as tools for data integrity. Although a few other tools have some of the same functionality, Google BigQuery is the …
Google BigQuery's main advantage over its direct competitors (Amazon Redshift and Azure Synapse) is that it is widely supported by non-Google software, while the others rely heavily on their own cloud ecosystems.
I have used other data manipulation tools like SQL Server and Google BigQuery feels more intuitive, Google provides so much documentation and tutorials that getting to know the software is not only easy but even satisfactory, so I'd say Google BigQuery is very superior to that …
Google BigQuery i would say is better to use than AWS Redshift but not SQL products but this could be due to being more experience in Microsoft and AWS products. It would be really nice if it could use standard SQL server coding rather than having to learn another dialect of …
Cost is the important factor for us compared with all of the other tools Google BigQuery stands top among all of them which charges very minimal charges for storage against all the apps that we have liked the most additionally, we can do query on our data, and can build …
Other locally hosted solutions are capable of providing the required level of performance, but the administration requirements are significantly more involved than with BigQuery. Additionally, there are capacity and availability concerns with locally hosted platforms that are a …
The biggest advantage that Looker Studio has is that it's really easy to use and to distribute to other use. You can have a really complex report set up in a couple of minutes with an extract data source that enables Looker to update really fast.
Looker was the most customizable option for our business and cost wise made the most sense. They do have a free tier option that some of the other weren't offering to us at the time. Looker has a great- mobile app solution while Tableau is a desktop-based platform. Tableau also …
Looker is less complex to use and links directly to google suite which we use across the business and personally think is a better user experience than microsoft.
Looker stacks up well against other data providers for usability and friendly interfaces, plus the ability to customise. We actually integrate Looker with other analytics tools in the same sphere (power bi, Dreamdata and others) so that we can have one comprehensive dashboard …
Verified User
Director
Chose Looker
In my opinion, Looker is no Power BI. It is good, but I think Power BI is amazing. That said, in my experience, Power BI is nowhere near as easy to setup and report on Google services as Looker is. We plan to continue using Power BI for c-suite and corporate reporting, …
If you company is using Google suite products, Looker is a no-brainer. Tableau is probably the most flexibly but as a result it has the least governance capabilities. Power BI is kind of old-school in terms of how it feels to use it. I think in general, Looker brings a lot of …
Better in terms of data configuration with slight harder learning curve, available help material is not that much and we usually have to connect with Looker Help with chat for our data and analysis questions. While Looker offers a wide range of visualization options, there were …
Technically, Power BI is much more complete and powerful, but it's like an ocean liner. I didn't need all that equipment. In my case, I needed to move more quickly, like on a speedboat, to build a page with several data sources in a single source of truth that could be easily …
The learning curve for Tableau Cloud was too steep for our team. After watching a couple of YouTube videos, anyone can begin connecting data sources and creating reports with Looker. Looker is also free with Google Workspace, making the decision between Looker and Tableau a …
There are some specific use cases where other tools are not useful in our organization. Some software solutions are shared with other organizations inside the company and Looker is the only tool where we can collaborate good enough.
Looker works and exists in the Google ecosystem. If you are a Google Cloud Platform user, Looker is a no brainer. There is also Looker Studio, the small (free) brother with less features which is basically a report only viewer/creator. The reason we choose Looker is because can …
Looker is a great fit for our company because we have collaborative analytics workflows and complicated data ecosystems and because of its strengths in data modeling, integration, and collaboration. Brand name and peer recommendations also helps us to select Looker against …
Our organization is going all in on Google products so switching out of the Microsoft suite of tools is a no brainer. All the Google tools work incredibly well together and once you transition it’s incredibly hard to be half in half out between Google and Microsoft. If you’re a …
We haven't had a proper benchmarking done. We might consider looking at other options, but this thing is deeply integrated into our platform, so not anytime soon.
Senior Manager, Digital Advertising & E-Commerce Team
Chose Looker
Google Looker Studio is an online tool for converting data into customizable, informative reports and dashboards. It is a free tool that turns performance data into informative, easy-to-read, easy-to-share, and fully customizable dashboards & reports. Google Looker Studio turns …
Actually, I use both power BI and Looker. Power BI has more data connectors and power query, one of the most important things that Looker does not have. You can customize the visuals in power bi in a higher level than Looker as well. Besides, Looker is much more advanced when …
Verified User
Manager
Chose Looker
Legitimately, every other business solution is superior to Microsoft's product offerings. They are a business that doesn't listen to their customers because they know that they don't have to and that someone will always be a client. That being said, Looker does care about your …
Complexity: Microsoft Power BI is more powerful and complex, Looker Studio is simpler and easier to use. Data: Microsoft Power BI handles complex data modeling and diverse sources, Looker Studio is better for simpler data and Google ecosystem sources. Analytics: Microsoft Power …
I prefer Power BI because of its affordability and fewer complicated tools than Tableau. It's easy to use and compatible with other Microsoft products, which are mostly used in the IT industry. It's not limited to only one platform like Looker Studio, which is mostly used in …
After several years using Google Looker Studio and BigQuery, Microsoft Power BI is a step-up in terms of visualizations. It is also much more powerful, leading to less errors and has a more intuitive interface. Looker Studio has a focus on Google Analytics whereas Microsoft …
Some of the strengths are 1. User-Friendliness 2. Self-Service BI (Caters to all levels of the employees 3. Cost-effective. 4. Easy integration with Microsoft Suits. 5. DAX Calculations 6. Familiar Interface like traditional Excel. 7. Easier Self-Service platform for …
Microsoft Power BI excels against its competition in being a great combination between feature set and scalability. Tableau is more integrated with Salesforce but it has a high starting price point whereas Microsoft Power BI can start out with a single license for less than $20 …
Verified User
Director
Chose Microsoft Power BI
Microsoft PowerBI is easy to use, has leadership alignment, and is liked by everyone using it in the past and in the current setup. Thus, we decided to continue renewing Microsoft Power BI. We had also evaluated some competitors, but those platforms were not as easy to onboard. …
Overall Microsoft Power BI has more capabilities, it is more customizable and it also has it's own query language DAX which is really powerful for complex calculations and that's something you just don't get in their competitors, also when integrated with the other power apps, …
Due to microsoft user and all the data into excel it was found more feasible from the organization to get Microsoft Power BI. Also due to access of microsoft licence we don't need to survey other vendors and feasibility. Also price wise it was more competitive then Tableau.
I selected Power BI because it is the best in all because of its ecosystem and its ability to connect with multiple data source like Microsoft Excel, Microsoft SQL Server, web, analysis services etc. Moreover, its available on both Cloud and Desktop with some pro and cons …
Director, eCommerce Analytics and Digital Marketing
Chose Microsoft Power BI
Power BI from a price perspective is the lowest cost (probably even from a total cost of ownership perspective) of all the offerings I have ever evaluated. The piece that really stands out for Power BI is the data transformation layer called Power Query. This section allows you …
Microsoft Power BI is the leader of this category, but it is a little expensive. It could use some more customization features, but other than that, it gives stellar returns for your investment.
We selected Microsoft Power BI because it was the easiest to integrate with our primary systems, allowed us to embed reports for our partners, allowed us to host our data and some reports on premise. It also provided the shortest route to production deployment allowing us to …
Microsoft BI tool does a better job than most of the other software. The reason is excellent visualizations and its capability to connect with various other software and data sources. Tableau does a better job when it comes to tutorials and being more user-friendly. Also …
We selected Power BI because it had more flexibility in modelling/measurement definition, excellent per-user pricing, easy self-implementation, integration with our other Office 365 tools, and easy distribution of content to others in the organization.
Power BI performs quite well in comparison to it's competitor's products. We compared it mainly to GoodData and Tableau. Power BI has a great pricing. It's affordable and efficient with mid-sized datasets. Hence many companies go for it. Competitive products like Tableau are …
Event-based data can be captured seamlessly from our data layers (and exported to Google BigQuery). When events like page-views, clicks, add-to-cart are tracked, Google BigQuery can help efficiently with running queries to observe patterns in user behaviour. That intermediate step of trying to "untangle" event data is resolved by Google BigQuery. A scenario where it could possibly be less appropriate is when analysing "granular" details (like small changes to a database happening very frequently).
When data drives potential for new orders, Looker earns its place in our tech stack. If, on the other hand, we are hoping for pipeline generation, Looker is useful if you are willing to repeatedly go check customer utilizations .... it is not appropriate if you are hoping to automate data analysis for this purpose.
Has significantly improved collation of data and visualisation especially with business across Europe. Has given me the ability to see the Site availability at the click of a button to see which Site is in the "money" and seize opportunities based on Market data
GSheet data can be linked to a BigQuery table and the data in that sheet is ingested in realtime into BigQuery. It's a live 'sync' which means it supports insertions, deletions, and alterations. The only limitation here is the schema'; this remains static once the table is created.
Seamless integration with other GCP products.
A simple pipeline might look like this:-
GForms -> GSheets -> BigQuery -> Looker
It all links up really well and with ease.
One instance holds many projects.
Separating data into datamarts or datameshes is really easy in BigQuery, since one BigQuery instance can hold multiple projects; which are isolated collections of datasets.
Show visited pages - sessions, pageviews - which programs are viewed the most.
Displays session source/medium views to see where users are coming from.
It shows the video titles, URLs, and event counts so we can monitor the performance of our videos.
It gives a graphic face to the numbers, such as using bar charts, pie graphs, and other charts to show user trends or which channels are driving engagement.
Our clients like to see the top pages visited for a month.
I like the drop-and-drag approach, and building charts is a little easier than it was before.
Options for data source connections are immense. Not just which sources, but your options for *how* the data is brought in.
Constant updates (this is both good and bad at times).
User friendliness. I can get the data connections set up and draft some quick visuals, then release to the target audience and let them expand on it how they want to.
Please expand the availability of documentation, tutorials, and community forums to provide developers with comprehensive support and guidance on using Google BigQuery effectively for their projects.
If possible, simplify the pricing model and provide clearer cost breakdowns to help users understand and plan for expenses when using Google BigQuery. Also, some cost reduction is welcome.
It still misses the process of importing data into Google BigQuery. Probably, by improving compatibility with different data formats and sources and reducing the complexity of data ingestion workflows, it can be made to work.
We have to use this product as its a 3rd party supplier choice to utilise this product for their data side backend so will not be likely we will move away from this product in the future unless the 3rd party supplier decides to change data vendors.
I give it this rating because it deems as effective, I am able to complete majority of my tasks using this app. It is very helpful when analyzing the data provided and shown in the app and it's just overall a great app for Operational use, despite the small hiccups it has (live data).
Microsoft Power BI is an excellent and scalable tool. It has a learning curve, but once you get past that, the sky is the limit and you can build from the most simple to the most complex dashboards. I have built everything from simple reports with only a few data points to complex reports with many pages and advanced filtering.
I think overall it is easy to use. I haven't done anything from the development side but an more of an end user of reporting tables built in Google BigQuery. I connect data visualization tools like Tableau or Power BI to the BigQuery reporting tables to analyze trends and create complex dashboards.
Looker is relatively easy to use, even as it is set up. The customers for the front-end only have issues with the initial setup for looker ml creations. Other "looks" are relatively easy to set up, depending on the ETL and the data which is coming into Looker on a regular basis.
Automating reporting has reduced manual data processing by 50-70%, freeing up analysts for higher-value tasks. A finance team that previously spent 20+ hours per week on Excel-based reports now does it in minutes with Microsoft Power BI's automated Real-time dashboards have shortened decision cycles by 30-40%, enabling leadership to react quickly to sales trends, operational bottlenecks, and customer behavior.
I have never had any significant issues with Google Big Query. It always seems to be up and running properly when I need it. I cannot recall any times where I received any kind of application errors or unplanned outages. If there were any they were resolved quickly by my IT team so I didn't notice them.
I think Google Big Query's performance is in the acceptable range. Sometimes larger datasets are somewhat sluggish to load but for most of our applications it performs at a reasonable speed. We do have some reports that include a lot of complex calculations and others that run on granular store level data that so sometimes take a bit longer to load which can be frustrating.
Somehow resources heavy, both on server and client. I recommned at least 50Mbs data rate and high performance desktop comouter to be abke to run comolex tasks and configure larger amount of data. On the other hand, the client does not need to worry when viewing, the performance is usually ok
BigQuery can be difficult to support because it is so solid as a product. Many of the issues you will see are related to your own data sets, however you may see issues importing data and managing jobs. If this occurs, it can be a challenge to get to speak to the correct person who can help you.
Never had to work with support for issues. Any questions we had, they would respond promptly and clearly. The one-time setup was easy, by reading documentation. If the feature is not supported, they will add a feature request. In this case, LDAP support was requested over OKTA. They are looking into it.
It is a fantastic tool, you can do almost everything related with data and reports, it is a perfect substitutive of Power Point and Excel with a high evolution and flexibility, and also it is very friendly and easy to share. I think all companies should have Power BI (or other BI tool) in their software package and if they are in the MS Suite, for sure Power BI should be the one due to all the benefits of the MS ecosystem.
PowerBI can connect to GA4 for example but the data processing is more complicated and it takes longer to create dashboards. Azure is great once the data import has been configured but it's not an easy task for small businesses as it is with BigQuery.
Looker Studio, you can easily report on data from various sources without programming. Looker Studio is available at no charge for creators and report viewers. Enterprise customers who upgrade to Looker Studio Pro will receive support and expanded administrative features, including team content management. So it's good.
Microsoft Power BI is free. If I didn't want to create a custom platform (i.e. my organization insisted on an existing platform that I *had* to use), I'd use Microsoft Power BI. For any start-up or SMB, I'd just use Claude & Grok to build it quickly, also for free. Would not pay for Tableau or Sigma anymore. Not worth it at all.
We have continued to expand out use of Google Big Query over the years. I'd say its flexibility and scalability is actually quite good. It also integrates well with other tools like Tableau and Power BI. It has served the needs of multiple data sources across multiple departments within my company.
Google Support has kindly provide individual support and consultants to assist with the integration work. In the circumstance where the consultants are not present to support with the work, Google Support Helpline will always be available to answer to the queries without having to wait for more than 3 days.
Previously, running complex queries on our on-premise data warehouse could take hours. Google BigQuery processes the same queries in minutes. We estimate it saves our team at least 25% of their time.
We can target our marketing campaigns very easily and understand our customer behaviour. It lets us personalize marketing campaigns and product recommendations and experience at least a 20% improvement in overall campaign performance.
Now, we only pay for the resources we use. Saved $1 million annually on data infrastructure and data storage costs compared to our previous solution.
Looker has a poignant impact on our business's ROI objectives. As an advertising exchange we have specific goals for daily requests and fill, and having premade Looks to monitor this is an integral piece of our operational capability
To facilitate an efficient monthly billing cycle in our organization, Looker is essential to track estimated revenue and impression delivery by publisher. Without the Looks we have set up, we would spend considerably more time and effort segmenting revenue by vertical.
Looker's unique value proposition is making analytical tools more digestible to people without conventional analytical experience. Other competing tools like Tableau require considerably more training and context to successfully use, and the ability to easily plot different visualizations is one of its greatest selling points.