It can be tempting when dealing with data grids to build custom components to suit your business needs, but at some point, you’ll reach a limit where there is no viable return on investment argument for coding your own component – you’ll save development budget and time by choosing a ready-made data grid.
At AG Grid we recently interviewed Proof Trading and Prisma for case studies, during which we learned the features they looked for in a data grid, and the evaluation processes they had followed, prior to choosing to use AG Grid in their systems.
For Proof Trading, key to their evaluation was having access to the community version of our code. The code is open-source and available on GitHub, allowing them to see the algorithms and techniques we used, and apply it hassle-free to their high frequency trading platform.
For Prisma, they were after a set of core features, alongside the ability to customise on the frontend, allowing them to implement their design vision and maximise their user experience (UX) aims.
The first point of evaluation when choosing a data grid is to ensure it has the core components: sorting, filtering, in cell editing, pagination and customising the rendering of data cells.
These should come as standard with any data grid, but at this stage it is also important to identify the volume of data that you need rendered in the grid as the data grid may not have been designed to cope with the amount you have in mind.
If you are expecting to handle high frequency updates, then the grid needs to support transactional updates and a virtualised Document Object Model (DOM) to avoid off screen updates.
After creating a list of basic features, it is important to explore the documentation provided with each grid to look for any extra features that may be useful, and to gauge the level of support should you need assistance with a grid.
Ideally, the desired grid will have rich documentation that showcases a variety of runnable examples so that developers can look at the code and experiment. These examples will also give a good feel for usability.
The ability to customise is a big draw, and ensuring your data grid has the level of customisation you require is important, whether it be custom cell renderers and editors, custom filters and sorting, or creating new CSS themes to style the grid.
An often-missed part of the evaluation criteria is searching for job listings specific to the data grid or component to gauge how easy it will be to recruit staff with relevant experience, as well as the popularity of the product in the marketplace.
When it comes to choosing a data grid, consider how easy it is to get started, with some providers you need to get permission from a sales team to set off and experiment, or whether the source code is stored in an open-source model.
During testing, developers like to review components from features, usability and quality of code standpoints.
That’s why AG Grid stores the code for our data grid on GitHub, all our code is available for review during an evaluation process. Also our community edition is MIT Licensed to allow developers to freely experiment and even release to production with no risk and no barrier to entry.
Choosing the right data grid for you may seem a daunting task, but by seeking out easily accessible, well-documented solutions, every business can find the data grid they need.
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