Spring '26 brought inline editing to the standard Flow Data Table, and people got genuinely excited about it. This is a feature admins and architects have been asking for since the component launched in Winter '23. It's a real step forward.

Here at Avonni, we've been building data table components for Screen Flows for several years now. We've spent a lot of time understanding what admins and users actually need from a table inside a flow — and we've learned that inline editing is just one piece of a much larger puzzle.

So here's the thing: this is our honest look at where both components stand today — so you can decide what fits your needs.

Getting data into the table

With the standard Data Table, you build a Get Records element, pull a collection, and pass it to the component. It's straightforward and works well for basic use cases.

The Avonni Data Table gives you another option: a built-in query data source with a visual query builder. You configure which records to display right inside the component — no separate Get Records needed. This also unlocks server-side filtering, which matters because it actually performs better on large datasets compared to filtering only on the client side.

Then there's how lookup fields show up. The standard component displays the raw record ID. To show the related record's name, you typically need formula fields, which work but add maintenance. Avonni traverses lookup relationships natively, showing names without the extra work.

Worth knowing: Avonni's query data source can simplify your flow canvas — fewer elements, fewer variables to manage.

What users see in each column

This is where the two components really start to differ.

The standard Data Table renders columns as plain text. It's clean and functional, but every column looks the same whether it's a status, an amount, or a percentage — everything shows as text.

The Avonni Data Table supports over 25 column display types:

→ Status fields as color-coded badges

→ Completion metrics as progress bars

→ Contact photos as avatars

→ Ratings, sliders, QR codes, barcodes, images, and auto-formatted currency

When users are scanning dozens of records, visual formatting helps them find what matters faster. A color-coded badge communicates priority at a glance in a way that plain text just doesn't.

Avonni also supports conditional cell coloring — changing backgrounds or text color based on data values — which gives admins another way to surface important information visually.

Worth knowing: Rich column types help users interpret data faster, especially in tables with many rows.

Inline editing — what Spring '26 brings and what's next

Credit where it's due — Spring '26 is a genuine milestone. After three years as read-only, the standard Data Table now lets users edit records inline. The community waited a long time for this, and it delivers.

Text, email, phone, number, currency, percent, checkbox — that's a solid range of editable field types. For everyday data cleanup and basic corrections, it'll be exactly what a lot of teams need.

So where does the Avonni Data Table go further?

→ Date pickers for updating deadlines or close dates inline — not yet available in Standard

→ Picklist dropdowns for changing statuses or stages from a dropdown — not yet available in Standard

→ Lookup field editing directly inside the table — not yet available in Standard

→ Per-column required field validation to enforce mandatory fields before submission — not yet available in Standard

→ Configurable numeric formatting — step sizes, decimal precision, fraction digits — not yet available in Standard

Is the gap narrower now? Absolutely — and we're genuinely glad to see it. A stronger standard component benefits admins everywhere. But we talk to teams every week whose workflows need date pickers, picklist dropdowns, lookup editing, and field-level validation. Those needs don't wait for the next Salesforce release — and with Avonni, they don't have to.

Worth knowing: Spring '26 covers a solid range of field types. For dates, picklists, lookups and validation, Avonni fills the gap today.

Search, filtering, and sorting

Both components now support a search bar and column sorting (sorting arrived in Standard with Spring '26). That shared foundation covers a lot of use cases.

The difference is in field-level filtering.

The standard component offers a global search bar. If your users need to narrow results by a specific field — showing only high-priority cases or filtering by stage — you have to build additional filter components in the flow.

Avonni includes a built-in filter panel where admins select which fields to expose as filter controls. Users can filter by specific columns right in the table. Combined with the query data source, filtering happens server-side, which is important for large datasets.

Worth knowing: If your users regularly need to slice data by specific fields, built-in filtering saves significant flow-building effort.

Actions and interactivity

This is an area worth paying attention to, because it shapes how users actually work with the table.

The standard Data Table supports row selection — multi-select, single-select, or view-only — and passes selected rows as output. For flows where the next step processes those selections, that's clean and simple.

The Avonni Data Table extends this with a full interaction framework:

→ Per-row action buttons and menus — Edit, Delete, View Details, Launch Sub-Flow

→ Header-level buttons — Create New Record, Export to CSV, Bulk Update

→ On-click interactions — update records, open a flow dialog, navigate to a page

The distinction really matters when the data table is the primary interface — not just a step, but the place where users spend their time. When users can take action directly from the table, they don't need to leave it. That changes everything about the workflow.

Worth knowing: If your users need to act on records — not just select them — row-level actions are a meaningful upgrade.

Data export

The standard Data Table doesn't support export right now. Avonni includes built-in CSV export — a straightforward feature that comes up a lot in operational workflows where users need to move data into a spreadsheet for reporting or sharing.

Configuration experience

The standard Data Table is quick to set up: drag it onto a screen, point it to a collection, and pick columns. Simple and familiar. The one limitation is there's no real-time preview — you configure the flow and then run it to see the results.

Avonni's Visual Component Builder gives you drag-and-drop configuration with a live preview. You see the table as you build it. It also supports reusable templates, which help teams standardize configurations across multiple flows.

For simple tables, the standard setup is perfectly fine. For complex tables with many columns, display types, and actions, a visual builder with live feedback cuts down the back-and-forth.

Worth knowing: The more complex your table, the more time a real-time builder saves you.

Row presentation and formatting

Some details that matter when users work in these tables every day:

Avonni supports row numbers, a record count in the header, and a selected count indicator — small touches that help users stay oriented in large datasets.

Column alignment and default width controls give admins layout precision. Number and currency columns support configurable formatting — fraction digits, step values, significant digits — so financial data renders consistently.

The standard component provides a clean, minimal presentation without these formatting controls.

Before you choose: architecture matters

One thing we always tell our customers: use the right tool in the right context.

If your goal is to display a rich data table on a Lightning record page or home page — and it's not part of a multi-step flow — embedding a Screen Flow just to host a table adds unnecessary overhead.

Screen Flows are designed for guided processes: wizards, data collection, and approvals. For standalone tables on Lightning pages, Dynamic Components are the better pattern. Avonni's Dynamic Components package lets you drop a fully interactive data table directly onto a page in App Builder — no flow wrapper, full reactivity.

Save Screen Flow data tables for what they excel at: data capture, bulk editing, and multi-step workflows where the table is one part of a guided process.

Let's talk about the elephant in the room

Yes, Avonni is a paid managed package. You're already paying a lot for Salesforce — we get it, and it's a fair concern.

Three things worth knowing:

1. First, it's free for orgs with fewer than 10 users. No trial, no time limit — full access.
2. Second, you're not paying for a data table. You're getting access to over 75 flow screen components — schedulers, steppers, kanban boards, rich forms, file uploaders, and dozens more. Each one is built with the same depth as the Data Table we've discussed here. It's an entire UI toolkit for Screen Flows.
3. Third — and this is the one that matters most — the real ROI isn't in what you save on development. It's in what your users save every day.

→ A service agent updating 20 cases after a call blitz: 10-15 minutes drops to under 2 with inline editing and row-level actions. Multiply that by 15 agents, five days a week.

→ A sales manager reviewing 50 opportunities: color-coded badges and conditional formatting mean 20 minutes of reading becomes 5 minutes of acting.

→ An ops team processing 100+ inventory adjustments weekly: inline date and number editing turns an hour-long task into 15 minutes.

These aren't edge cases. These are on Tuesday morning.

When you do that math for your own team, the ROI usually answers the pricing question on its own. The investment isn't in software — it's in your team's daily experience on Salesforce.

First, it's free for orgs with fewer than 10 users. No trial, no time limit — full access. Available on AppExchange

Choosing what's right for your team

The standard Data Table is a solid component that continues to improve. Spring '26 is the most significant update since launch, and Salesforce is clearly investing in its evolution. For flows where you need to display records, allow basic edits, and pass selections downstream — it's a capable, zero-cost option with no dependencies.

The Avonni Data Table exists because we've spent years listening to admins who needed more — rich visual formatting, editing across all field types, row-level actions, built-in filtering, conditional formatting, data export, and a real-time builder. These aren't theoretical features; they're solutions to problems our customers face every day.

We're genuinely glad to see Salesforce investing in the standard Data Table. A stronger native component raises the bar for everyone — including us. It pushes us to keep building what admins need next.

We hope this comparison helps you make the right call for your team. Both tools have their place. The key is knowing what each one offers so you can match it to what your users actually need.

‍