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)
Kintone
Score 9.9 out of 10
N/A
Kintone is a customizable digital workplace platform used to manage data, tasks, and communication. The no-code drag-and-drop interface can be used to create custom applications.
$120
per month per user (minimum 5 users)
Pricing
Google BigQuery
Kintone
Editions & Modules
Standard edition
$0.04 / slot hour
Enterprise edition
$0.06 / slot hour
Enterprise Plus edition
$0.10 / slot hour
Professional Subscription
$24
per month per user
Offerings
Pricing Offerings
Google BigQuery
Kintone
Free Trial
Yes
Yes
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
Optional
Additional Details
—
All subscriptions have a minimum requirement of 5 users.
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).
Kintone is great if you want a software that will help you in managing your data, and keep track of which tasks are assigned to whom. It also helps to streamline communication and information in one central place. However, it is not for you if you are looking for something complex that has to manage a lot of 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.
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.
I feel that Kintone is not well enough known yet. This means that other apps/APIs are not necessarily easy to connect with Kintone. Yes, you can use Zapier though for interfacing with other apps.
It would be great if it could give more customized options to change the look and format of certain things. You can make price quote apps, for example, but have to rely on 3rd party apps or programming skills to customize the look and fields.
If you make a table as an input field, it cannot connect to other internal Kintone apps for lookups and such.
I think there is more potential to make more customized data graphs.
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 still think that there's a room for Kintone's future, and high expectations for them in additional features and innovative tools and supports. Truly hope that they will support email features, and standardized supports for various plug-ins with the 3rd party software and apps. In the meantime, we will have to consider our ways of doing our work in all aspects
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.
Kintone is agile app and most of the time we can easily come up with new apps. However, there should be more feature-based drag and drop and or a visual-based usability, as we all want to minimize the number of clicks and dropdown menu selections as much as possible. Thanks.
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 have had very specific questions about different aspects of the software, and I have always been able to get a hold of someone who could help. If my sales rep didn’t know the answer, he would get me in touch with someone who did know the answer. The whole team is very ready to help. It definitely feels like they view my success as their success, which is so important with this type of software.
Everyone has their own tastes of things and way they want to work. Asking them to adapt to the changes with the new tools or apps is always difficult. We would want to start with a very small but best example within the organization, which in our case was that the employees will not be bothered by the bosses by being asked to find the documents, status of the progresses, or major things/requests/projects.
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.
Kintone is the easiest product to create from and the cost is the lowest I believe. In addition, reconfigurability and extendability are great. If you look for a low code tool, you can try Kintone. But as same as another low code tool, don't expect too much.
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.
