
NowCerts
Jenesis Software
BindHQ
Partner XE
HawkSoft CMS
Nexsure
Guidewire PolicyCenter
CRM/Agency Management System for L&H Insurance Agencies

AG Grid
Hashnode
FathGrid
Chart.js
DataTables
D3.js
React
A grid library for instant big data processing.

Which is more popular?
Based on our record, DataTable.dev seems to be more popular. It has been mentioned 1 time since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | agencybloc.com | datatable.dev |
| Pricing | — | |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of AgencyBloc yet.
DataTableDev is a grid with maximum speed and efficiency. Developed to display and analyze millions of rows in a split second, it will be a true find for an effective data visualization. Based on a new technology, this grid instantly handles and shows gigabytes of your data. At once, users...
What each product offers, as listed by its team.


Possible disadvantages
No features have been listed yet.
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
AgencyBloc is recommended for small to medium-sized insurance agencies that require a CRM platform to manage clients, policies, and operations efficiently. It is particularly useful for agencies looking for a solution that combines CRM functionality with marketing, sales, and service automation to improve overall business performance.
No analysis of DataTable.dev yet.
Walkthroughs and reviews on video.
AgencyBloc Review: Matt Tharp
More videos
DataTable.dev - a grid component to process & show big data on-the-spot
How often each product is chosen within a category, 0–100% relative to the other.


Share your experience with using AgencyBloc and DataTable.dev. For example, how are they different and which one is better?
Recommendations tracked on public social media and blogs since March 2021.


Tracking AgencyBloc since Mar 2021.
Hey Reddit! It’s DataTable.dev here - a JavaScript grid component that can instantly handle any amount of data. We managed to create an approach to working with such tabular data providing our users with ideal performance regardless of... Source: about 3 years ago
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