Databox is business intelligence software built for teams that need fast, actionable insights.
$199
per month
Google BigQuery
Score 8.8 out of 10
N/A
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
Pricing
Databox
Google BigQuery
Klipfolio Klips
Editions & Modules
Professional
$199
per month
Growth
$499
per month
Premium
$999
per month
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
Offerings
Pricing Offerings
Databox
Google BigQuery
Klipfolio Klips
Free Trial
Yes
Yes
Yes
Free/Freemium Version
No
Yes
No
Premium Consulting/Integration Services
No
No
Yes
Entry-level Setup Fee
No setup fee
No setup fee
Optional
Additional Details
20% discount for annual pricing.
—
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
Databox
Google BigQuery
Klipfolio Klips
Features
Databox
Google BigQuery
Klipfolio Klips
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Databox
9.3
8 Ratings
13% above category average
Google BigQuery
-
Ratings
Klipfolio Klips
9.0
33 Ratings
11% above category average
Pixel Perfect reports
10.05 Ratings
00 Ratings
9.13 Ratings
Customizable dashboards
8.98 Ratings
00 Ratings
8.933 Ratings
Report Formatting Templates
8.98 Ratings
00 Ratings
9.13 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Databox
8.6
8 Ratings
7% above category average
Google BigQuery
-
Ratings
Klipfolio Klips
8.6
33 Ratings
10% above category average
Drill-down analysis
8.06 Ratings
00 Ratings
8.35 Ratings
Formatting capabilities
8.98 Ratings
00 Ratings
7.85 Ratings
Integration with R or other statistical packages
7.93 Ratings
00 Ratings
9.12 Ratings
Report sharing and collaboration
9.48 Ratings
00 Ratings
9.133 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Databox
8.3
8 Ratings
1% above category average
Google BigQuery
-
Ratings
Klipfolio Klips
9.4
33 Ratings
14% above category average
Publish to Web
8.96 Ratings
00 Ratings
8.931 Ratings
Publish to PDF
8.97 Ratings
00 Ratings
9.228 Ratings
Report Versioning
7.74 Ratings
00 Ratings
00 Ratings
Report Delivery Scheduling
8.98 Ratings
00 Ratings
10.017 Ratings
Delivery to Remote Servers
7.13 Ratings
00 Ratings
00 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
I believe Databox can be an asset for any company. We are a small company, but I can see the value for large companies too. Databox is a great fit for departments or organizations that need to put their data into a readable form without needing a ton of reports. Databox allows you to save time and put together a nice report without having to do too much extra work. Once it is set up, it basically runs on its own at the frequency you set. I personally receive a daily report and have it sent to the respective people on the day of our meeting so we can quickly review it.
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.
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.
Some types of data can only be reported on for 1-2 months back. Unless I'm misunderstanding the function of the software this seems really weird. I can't figure out how to report on Activities more than 2 months ago
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.
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.
Databox is an intuitive, well-designed platform that can be used by non-technical marketers. It is easy to learn, and while set up takes time, usability is high and the team has enjoyed creating custom dashboards and clients have also given us great feedback regarding its usability and value. While other BI tools are much more complex to navigate, Databox is a breeze.
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.
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.
I have really enjoyed using Databox and have seen the value of it in many ways. They also continue to improve the functions of it and grow their integrations and templates. I look forward to continuing to use Databox in the future, potentially even finding ways to incorporate it into other departments to help them with reporting as well.
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.
Databox is unique in its ability to report from multiple data sources. Google Analytics is the standard when it comes to web metrics, but it's just one of the tools that integrates with Databox. Tableau is fantastic for data visualizations and reporting, but it's much more expensive than Databox, so it's not ideal for everyone. Tableau is also superior with customization
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.
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.