Few questions about the product
want to integrate this tool in my app and I have few questions if I may.
- I went through some of the samples and they are all working in a small dataset.
What happens when I want to analyze 500K + rows, it is not so optimized for browser in-memory work. (not mentioning the download time).
Is there a solution for server-side rendering of partial relevant data? I can think of several different approaches… for example, the client-side instruct the server how to aggregate the data and the server returns only the aggregated data, do you have solutions for that large dataset?
Google data studio actually works like that
- What is the status of the project, it is not an open-sourced, we can’t really see contributors, commits releases and so on.
- besides rendering technology, what is the difference between this amazing tool and google data studio?
Thank you for your questions.
- Our team would like to kindly inform you that the data size WebDataRocks can handle is limited to 1 MB. If your needs require larger data sets we can recommend checking on Flexmonster which is a premium pivot table component developed by the same team.
Also, Flexmonster is simply connected with Microsoft Analysis Services, Mondrain, Elasticsearch and custom source API. That will allow you to render only required part of your data.
- WebDataRocks is a free solution developed and supported by the Flexmonster team. WebDataRocks’es new releases are the migration of some Flexmonster features. Please note that there is no exact ETAs for WebDataRocks’es releases. At the same time, Flexmonster provides release notes for each minor update (every 2 weeks), improved support and exclusive features for clients.
- The main difference between WebDataRocks and Google Data Studio is that Google offers the full solution when WebDataRocks is only a client-side component.
More differences can be found using specifications: https://www.webdatarocks.com/doc/technical-specifications/.
Feel free to contact us in case of additional questions.