Google BigQuery vs. Looker

Google BigQuery is great for being the central datastore and entry point of data if you're on GCP. It seamlessly integrates with other Google products, meaning you can ingest data from other Google products with ease and little technical knowledge, and all of it is near real-time. Being serverless, BigQuery will scale with you, which means you don't have to worry about contention or spikes in demand/storage. This can, however, mean your costs can run away quickly or mount up at short notice.

Incentivized

When you need to create a centralised dashboard for multiple stakeholders that blends cross-channel reporting. As an SEO agency reporting for clients - Looker is a great solution. It's less appropriate depending on the intended users. For instance, in my experience Looker reports have been under-utilised because they're not accessed regularly, provide too much noise or often simple PDF reports are preferred

Incentivized

• Its serverless architecture and underlying Dremel technology are incredibly fast even on complex datasets. I can get answers to my questions almost instantly, without waiting hours for traditional data warehouses to churn through the data.
• Previously, our data was scattered across various databases and spreadsheets and getting a holistic view was pretty difficult. Google BigQuery acts as a central repository and consolidates everything in one place to join data sets and find hidden patterns.
• Running reports on our old systems used to take forever. Google BigQuery's crazy fast query speed lets us get insights from massive datasets in seconds.

Incentivized

• It is very easy to start a new dashboard and configure what you want to display by just selecting/dragging from the list of available columns.
• It is intuitive, mainly if you use other Google services like Google Sheets.
• The look and feel is modern and nice.
• It it very useful to have an immediate visual overview of the data in a spreadsheet.

Incentivized

• It is challenging to predict costs due to BigQuery's pay-per-query pricing model. User-friendly cost estimation tools, along with improved budget alerting features, could help users better manage and predict expenses.
• The BigQuery interface is less intuitive. A more user-friendly interface, enhanced documentation, and built-in tutorial systems could make BigQuery more accessible to a broader audience.

Incentivized

• I wish I could get more granular in the Google ad data, such as down to the campaign type, instead of having to see only all campaigns.
• The setup can be time-consuming if you're not using the product regularly.
• Editing the dashboard requires a few logins; I wish it was more seamless.

Incentivized

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.

Incentivized

We are very haooy with Looker, it provides us with all the funciomalities we need for both the day to day oerformance tracking and longer periods reporting. It is easy to use for account managers, configurable and customizable for soecialists and what is most imoortant, our clinets generally really love it

Incentivized

web UI is easy and convenient. Many RDBMS clients such as aqua data studio, Dbeaver data grid, and others connect. Range of well-documented APIs available. The range of features keeps expanding, increasing similar features to traditional RDBMS such as Oracle and DB2

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.

Incentivized

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.

Incentivized

No objections

Incentivized

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.

Incentivized

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

Incentivized

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.

Incentivized

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.

Incentivized

Very satisfied, easy to implement

Incentivized

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 external sources (like CRM tools), so our analytics can be unified. Due to our heavy reliance on GA4, Google BigQuery is the natural choice since it is a Google product and has better integration.

Incentivized

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, especially for internal databases, but will gladly use Looker for our marketing information for AdWords, Analytics, Search Console, and YouTube.

Incentivized

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.

Incentivized

• In some places, Google BigQuery has helped us save some money by avoiding the need for expensive infrastructure and reducing some of the operational costs.
• Scalability is up-to-date and really helpful in multiple places.
• Knowledge transfer is easy as it is very user-friendly, so the learning curve has been reduced.
• Also, it gives us more insights from our data, helping us make smarter decisions for our business.

Incentivized

• Other than some people not liking the numbers, I don't see any negative impacts; we haven't experienced that.
• The reports help us unravel the story of our users and how they are sifting through our pages.
• Our clients enjoy seeing the numbers to understand better what stands out on their sites.
• The reports have helped us see what campaigns are working and where we need to tweak things.
• The reports have enabled us to have better conversations with stakeholders about how their web pages should be modified, edited, etc., to reflect the data.

Incentivized