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 Studio
Score 8.1 out of 10
N/A
Looker Studio is a data visualization platform that transforms data into meaningful presentations and dashboards with customized reporting tools.
$9
per month per user per project
QlikView
Score 8.2 out of 10
N/A
QlikView® is Qlik®’s original BI offering designed primarily for shared business intelligence reports and data visualizations. It offers guided exploration and discovery, collaborative analytics for sharing insight, and agile development and deployment.
N/A
Pricing
Google BigQuery
Looker Studio
QlikView
Editions & Modules
Standard edition
$0.04 / slot hour
Enterprise edition
$0.06 / slot hour
Enterprise Plus edition
$0.10 / slot hour
Looker Studio Pro
$9
per month per user per project
Looker Studio
No charge
QlikView
Custom
per user
Offerings
Pricing Offerings
Google BigQuery
Looker Studio
QlikView
Free Trial
Yes
No
Yes
Free/Freemium Version
Yes
Yes
No
Premium Consulting/Integration Services
No
No
Yes
Entry-level Setup Fee
No setup fee
No setup fee
Optional
Additional Details
—
—
On an perpetual license basis, based on server plus number of users.
Contact vendor for pricing.
More Pricing Information
Community Pulse
Google BigQuery
Looker Studio
QlikView
Considered Multiple Products
Google BigQuery
Verified User
Manager
Chose Google BigQuery
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 …
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 …
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.
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 …
BigQuery has a simpler and more intuitive user experience (as is the case with most of its products) compared to AWS, which has a more technical and complex profile, so it was the first tool we used. It's still my go-to option for handling SQL queries, though it doesn't detract …
Google Data Studio is widely available and accessible, can be shared easily, and it only takes 20-30 min to build a rudimentary dashboard. It has very little setup and does not rely on internal data architecture and development. For later development purposes, Tableau, Power …
We selected Google Data Studio because it is easier to make connections with third-party data sources. Also Google Data Studio can understand connections between different tables and databases better that its competitors such as Power BI. Compared to Power BI you do not need to …
Verified User
C-Level Executive
Chose Looker Studio
We are heavily within the Google ecosystem and therefore didn't really consider alternatives to Google Data Studio since it met our somewhat limited needs at the time of implementation. For outside presentations, we would probably lean towards something that allows us to more …
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).
Visualizing cross-channel campaign performance can blend data from a few different sources to compare performance metrics like spend, clicks, and conversions side-by-side in a single view, which helps in quick budget reallocation decisions. When dealing with massive volumes of data (millions of rows) or highly complex queries, Looker Studio dashboards can become slow, laggy, or even crash. Performance issues are a frequent complaint when working with large datasets, making it unsuitable for enterprise-level companies
Sales data validations have helped manage our justifications in the past, especially with regard to new product development and new business introduction. It has also been helpful in identifying trends with business impact and direction specific to quarter and monthly sales from ERP data as well as decisions to purchase equipment of staffing based on run rates and product demand.
One thing that can get out of hand is data output - if you aren't careful in your query, you may be overloaded with data dumps and drown in the amount of info you have to filter through. This is a user caution, not a comment on the software itself.
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.
Breath of data - the number of ways to interrogate the data is endless, and the options to view metrics alongside each other make for comprehensive datasets.
Data visualisation and customisation - the options for presenting data and separating out across pages allow for clean visuals and segmented information.
Easy shareability/usability - a quick and simple tool to introduce colleagues to, and easy to grant access for them to be able to view the data, without having to understand the setup itself.
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.
It needs better handling of complex logic. We often need workarounds to perform complex custom calculations, and it can be really unpleasant at times.
Felt it got slow with a larger data set, and in one minor report, we had to set up time filters so that calculations during spikes could be traced more quickly.
Compare to competition they need to improve with notification things.
We found that QlikView can be a bit slow in supporting some forms of encryption. It is web-based and we needed to upgrade all of our server to not support the older SSL and TLS 1 protocols, only support TLS 1.2 and TLS 1.3. However, QlikView could not run with TLS 1.2 and TLS 1.3. We had to wait over six months to get a version that would handle the newer TLS versions.
There are so many options with QlikView that you can get lost when developing a visualization. There are still items I have not yet figured out, such as labeling a graph with the name of a selected detail item.
QlikView works by pulling the data it is going to use for visualization into its database. I am a security reviewer and I need to make certain that PII and PHI is not pulled by QlikView for a visualization, otherwise this could become a reportable indecent.
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.
It is the simplest and least expensive way for us to automate our reporting at this time. I like the ability to customize literally everything about each report, and the ability to send out reports automatically in emails. The only issue we have been having recently is a technical glitch in the automatic email report. Sadly, there is almost no support for this tool from Google, but is also free, so that is important to take into consideration
Ease of use, ability to load from pretty much any data source. today I created an application that loaded time sheets from excel that are not in a table format. With Qlik's "enable transformation steps" I was able to automate loads of multiple spreadsheets and multiple tabs easily. Could not do that with any other tool.
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 Studio is easy to use, and it offers a sufficient variety of predefined visualizations to choose from. It's easy for us, and anyone can set up basic reporting without extensive data visualization skills. The interface layout is easy to understand, and it doesn't take long to get used to.
QlikView is very easy to implement. The installation is very straight forward. QlikView has several different data connectors that can connect to different data sources very smoothly. The user interface to build the reports is very easy to understand. This helps to have a smaller learning curve. Something very helpful is that QlikView is a browser application for the end users. So, you don't need to install any applications on the user's computer.
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.
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.
I give it a lower support rating because it seems like our Dev team hasn't gotten the support they need to set up our database to connect. Seems like we hit a roadblock and the project got put on pause for dev. That sucks for me because it is harder to get the dev team to focus on it if they don't get the help they need to set it up.
My experience with the Qlik support team has been somewhat limited, but every interaction I have had with them has been very professional and I received a response quickly. Typically if there is a technical issue, our IT team will follow up. My inquiries are specific to product functionality, and Qlik has been very helpful in clarifying any questions I might have.
My team attended, but I cannot myself rate, but I think it was good as they've successfully launched a training program at our company themselves for users. It was 3-4 day training.
Training was as expected. The demo environments tend to be more fully featured that our own environment, but the training was clear and well delivered.
"Implementation" can mean a few things... so I'm not sure that this is the answer you want.... but here it goes: To me, implementation means: "Is the user interface intuitive and can I produce meaningful reports with ease?" On that score, I'd say YES. The amount of training required was minimal and the results were powerful. The desktop implementation is a simple, "blank" interface just waiting for your creativity. The pre-populated templates give you a reasonable start to any project -- and a good set of objects to "play around with" if you're just getting started. Finally, note that the "implementation" I used was baked into QuickBooks 2016 Enterprise -- called "Advanced Reporting"..... That integration makes it ultra useful and simple.
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 is far easier to implement, stand up, and learn. The interface is simpler and user-friendly for various levels of data visualization/analysis knowledge and experience. The biggest benefit of Looker Studio, however, is its ease of connection to GA data and speed. Furthermore, since it is an online program/tool, it requires less CPU/battery/storage on the user's device.
The only other vendor product that I have worked with that provides a similar experience to Qlikview is Tableau. I would recommend Tableau if your use case is to build a fixed dashboard. You can share reports for free without needing to buy additional licenses. I would recommend Qlikview if your users are looking for a more interactive experience. They can create new objects to represent the data which can't be accomplished as easily in Tableau
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.
You can use the free desktop version to do a lot of reporting and analysis work more quickly so the ROI is huge
QlikView is great at finding outliers such as data entry errors
QlikView is great at helping you quickly discover new insights about your business that can prompt you to take action that can immediately affect your cash flow.
