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)
Klipfolio Klips
Score 9.2 out of 10
Small Businesses (1-50 employees)
Klipfolio is a customizable dashboard and reporting platform that provides real-time business insights. It is used by small to mid-sized businesses and agencies to track performance metrics and create tailored reports, and to consolidate, transform, and visualize data.
$90
per month
Looker Studio
Score 8.2 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
Pricing
Google BigQuery
Klipfolio Klips
Looker Studio
Editions & Modules
Standard edition
$0.04 / slot hour
Enterprise edition
$0.06 / slot hour
Enterprise Plus edition
$0.10 / slot hour
Base
$90
per month
Grow
$190
per month
Team
$350
per month
Looker Studio Pro
$9
per month per user per project
Looker Studio
No charge
Offerings
Pricing Offerings
Google BigQuery
Klipfolio Klips
Looker Studio
Free Trial
Yes
Yes
No
Free/Freemium Version
Yes
No
Yes
Premium Consulting/Integration Services
No
Yes
No
Entry-level Setup Fee
No setup fee
Optional
No setup fee
Additional Details
—
Discount available for annual pricing. There are various implementation and training options available, from a 60 Day Proof of Concept, to Onboarding & Training, or ongoing dedicated Data Hero support.
—
More Pricing Information
Community Pulse
Google BigQuery
Klipfolio Klips
Looker Studio
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 …
Over the years, I have been required to work with other platforms to collect and analyze data for a variety of ad agencies and clients that I have worked with. It really came down to a Goldilocks comparison where we consistently found that dashboard platforms were bloated with …
Klipfolio had the best API. We could connect more MarTech with Klipfolio than any other BI tool we used. Klipfolio's API was also the most stable. We ran into connectivity issues with some of the competitors. The metrics wouldn't refresh because the API lost the connection …
Web Analytics and Data dashboarding (consulting mandate)
Chose Klipfolio Klips
Klipfolio is certainly the best solution for dashboards. Compared to Power BI, Power BI is more of an analyst tool to build deep analysis and reports. Making and sharing dashboards in Power BI is a pain. Tableau is great but cost way more. Also, the skills needed to build …
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).
Using Klipfolio is one of the finest ways we can expand our business because it is so simple to use and always has new features that make it better. We also appreciate the excellent customer service they offer. There are several benefits to making this investment in your company's efficiency and profitability. We think it's worth the money.
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
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.
While Klipfolio covers so many of the bases, one area where I would like to see expansion would be offering additional design and graphics themes for even more customization.
Klipfolio has an extensive offering but might be even better if there were a way that we could integrate with some small to mid-sized CRM solutions for audience list segmentation and marketing integrations.
It would be interesting if Klipfolio could enable us to overlay the data learnings for cross-referencing of multiple client campaigns for comparative insights.
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 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
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.
My initial impressions of the software have been extremely positive. There are YouTube tutorials that explain how to make klips. The intuitive design of the UI It appears that everything in this software has been thoroughly tested to create all the visualizations that can be imagined as well as the user input controls that allow users to have exactly the data they want to be displayed in seconds, considering the various functions and formulas available in the Excel integrations and the extensive list of other services that can be integrated.
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.
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.
It provides all the necessary information to be able to carry out the analysis of any type of business, to know how money is managed virtually, what to do to have greater visibility, in addition to being a platform that is always accessible and allows continuous and efficient work.
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.
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.
These and many other BI tools are the most direct competitors. I only have experience with Klipfolio and Tableau. Tableau is definitely more capable, but much more difficult to learn and use. Klipfolio is simple and really packs a punch for its simplicity. I have yet to run into a major problem with it lacking a needed functionality.
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.
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.
