Top 3 SQL & external data apps for Atlassian Confluence Cloud

May 22, 2026

7 min

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Disclosure

PocketQuery is built by Lively Apps, the publisher of this blog. We've done our best to keep the comparison fair and source it from each vendor's public Atlassian Marketplace listing and documentation. Where you think we got something wrong, tell us and we will update the post.

Hi there,

If your team needs live SQL data on a Confluence page, three apps come up over and over when evaluating your options: PocketQuery by Lively Apps, SQL for Confluence (Pro Edition) by Appfire, and External Data for Confluence by codefortynine. We put them through a detailed comparison so you don't have to.

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TL;DR

PocketQuery is the only one of the three with native Snowflake and BigQuery support, a built-in chart engine, a Velocity / HTML / JavaScript template layer, a sandboxed JavaScript result converter, and the lowest price at every paid tier. Appfire is the most institutionally mature option but limited to MSSQL, PostgreSQL and MySQL on Confluence Cloud, with no chart engine, no templating and no result converter. External Data for Confluence offers strong native Snowflake support and a broad set of named SaaS connectors, paired with its own JavaScript converter and HTML template feature.

If you've ever tried to show live data in Confluence...

Atlassian Confluence Cloud is great for unstructured content. It's not built for pulling data out of a SQL database and showing the result on a page. Teams that want runbooks, KPI overviews, on-call dashboards, customer 360 pages or release reports backed by real numbers always end up on the Atlassian Marketplace.

This article compares the three Marketplace apps that come up most often: PocketQuery by Lively Apps, SQL for Confluence (Pro Edition) by Appfire, and External Data for Confluence by codefortynine. For each app we cover the vendor, Marketplace install count, supported databases (including big-data warehouses), visualisation and templating, result conversion, the permission model across three levels (admin, space, user), and the actual pricing from the Marketplace pricing calculator.

The three apps, named and verified

Every row was checked directly against the Atlassian Marketplace listing.

App	Vendor	Installs (Marketplace)
PocketQuery, Connect SQL Databases & REST in Confluence	Lively Apps (Atlassian Silver Marketplace Partner)	860
SQL for Confluence (Pro Edition)	Appfire (Atlassian Platinum Marketplace Partner)	1,103
External Data for Confluence	codefortynine (Atlassian Platinum Marketplace Partner)	329

‍*Install counts are the figures shown on each listing at the time of writing. They include free trials, so read them as order of magnitude rather than exact customer counts.

Big Data

A SQL reader is only useful if it can reach the systems where your data actually lives. For many teams in 2026 that means a warehouse or lakehouse: Snowflake, Google BigQuery, Amazon Redshift, Databricks, and increasingly column-store engines like ClickHouse. Traditional enterprises also still keep critical data in SAP HANA and IBM Db2. The table below maps every big-data target named on each app's Marketplace listing or vendor documentation.

Big data platform	PocketQuery (Lively Apps)	SQL for Confluence Pro (Appfire)	External Data for Confluence (codefortynine)
Snowflake	✅ Native	❌ No	✅ Native
Google BigQuery	✅ Native	❌ No	✅ Indirect (via the REST API datasource)
Amazon Redshift	✅ Indirect	❌ No	✅ Indirect
Databricks (SQL Warehouse / Lakehouse)	❌ No	❌ No	❌ No
Azure Synapse Analytics	✅ Reachable through the MSSQL driver	✅ Reachable through the MSSQL driver	✅ Reachable through the MSSQL driver
ClickHouse	❌ No	❌ No	❌ No
SAP HANA	✅ Native	❌ No	❌ No
IBM Db2 / Db2 for i	✅ Native (both)	❌ No	✅ Db2 listed
MongoDB	❌ No	❌ No	❌ No
Elasticsearch	✅ Indirect (REST API)	❌ No	✅ Indirect (REST API)
Generic REST API	✅ Native	❌ No	✅ Native
Salesforce, SharePoint, HubSpot, Airtable	✅ Reachable via REST	❌ No	✅ Native (named in the listing)

PocketQuery and External Data for Confluence both support Snowflake natively. PocketQuery also names BigQuery as a native SQL datasource. Appfire's SQL for Confluence Pro lists only Microsoft SQL Server, PostgreSQL and MySQL - which rules it out for warehouse-first teams in 2026.

PocketQuery is the only app that names SAP HANA, IBM Db2 and IBM Db2 for i, which matters if your data lives in mainframe-adjacent or SAP-anchored systems.

On SaaS sources (Salesforce, SharePoint, HubSpot, Airtable), External Data for Confluence ships explicit named connectors. PocketQuery reaches the same surface through its generic REST Datasource (Basic Auth, OAuth 2.0, custom headers) - slightly more setup, but the same REST-reachable universe.

Diagram engine, templating, and result conversion

A built-in diagram engine, a templating layer, and a result converter decide whether a SQL reader stays at "rows on a page" or becomes a real reporting layer inside Confluence.

Visualisation possibilities	PocketQuery (Lively Apps)	SQL for Confluence Pro (Appfire)	External Data for Confluence (codefortynine)
Built-in diagram / chart engine	✅ Yes, native Chart API for bar, line, pie and KPI visuals.	❌ No, the listing only describes dynamic tables with sort, filter, row highlighting and pagination.	✅ Yes, native bar, line and pie charts with multiple data sets.
Templating	✅ Yes, Velocity, HTML and JavaScript templates that can be layered on top of any Query result.	❌ No, table styling only.	✅ Yes, a custom HTML "Template" feature, marketed as "advanced tables".
Built-in result converter	✅ Yes, a full JavaScript engine running inside a sandbox, plus column-level formatting for dates, numbers and currency.	❌ No, formatting is table presentation, not a result transformer.	✅ Yes, an explicit "Convert data with JavaScript" feature for transforming results before rendering.

Both PocketQuery and External Data for Confluence ship a sandboxed JavaScript engine for transforming query results. PocketQuery layers column-level formatting (dates, numbers, currency) on top of that, and supports Velocity, HTML and JavaScript in its template layer. External Data for Confluence pairs its JavaScript converter with a custom HTML Template feature. Appfire's SQL for Confluence Pro stops at tables - no chart engine, no templating, no result converter.

Permission model: admin, spaces, users

A SQL reader on a Confluence page is also a permissions surface. Three layers matter: who configures the connection (admin), where the macro is allowed to be used (space), and who can author, run, or just view the results (user).

Layer	PocketQuery (Lively Apps)	SQL for Confluence Pro (Appfire)	External Data for Confluence (codefortynine)
Admin level	Datasources are admin-only. Credentials are configured in the global app admin and never exposed on the page.	Admins configure connection profiles in the global app admin. Each profile has its own access settings.	Datasources are configured in the global app admin.
Space / per-resource level	Each Query can be restricted to one or more Confluence spaces, so a Query only renders inside the spaces it has been published to.	Per-data-source access settings let admins limit which users a profile is exposed to.	Restrictions are applied via the broader Atlassian Confluence permissions on the pages where the macro is embedded.
User level	Two role groups, PocketQuery Admin (can create and edit any entity, including Datasources) and PocketQuery Editor (can create and edit Queries, but cannot create or edit Datasources). Both are mapped to Confluence user groups. Crucially, the PocketQuery Admin group is independent of the Confluence site-admin group, so SQL governance can be delegated to a data team without granting site-level Atlassian admin rights.	User permission settings on top of the profile model, so admins can decide which users can use which profile in the macro editor.	The macro respects Atlassian Confluence page-level permissions. The app does not document a separate user-level role model on top of Confluence's own roles.

PocketQuery splits the world cleanly: admins own Datasources and credentials, Editors write Queries against those Datasources, and each Query can be scoped to specific Confluence spaces. Since the PocketQuery Admin role is its own user group, separate from the Confluence site-admin group, your data team can manage SQL governance without having to handle site-level admin rights. Appfire layers user permission settings on top of admin-defined profiles. External Data for Confluence keeps configuration at the admin level and leans on Confluence's native page and space permissions for everything user-facing.

Pricing in comparison

These numbers come straight from the Atlassian Marketplace pricing calculator on each app's listing, for Cloud. Each cell shows monthly / annual in USD. Atlassian's annual price is exactly 10× the monthly rate, so paying annually is effectively two months free on any of these apps.

Team size	PocketQuery (Lively Apps)	SQL for Confluence Pro (Appfire)	External Data for Confluence (codefortynine)
	mo / yr	mo / yr	mo / yr
Up to 10 users	Free	Free	Free
25 users	$10.75 / $107.50	$36.75 / $367.50	$18.75 / $187.50
50 users	$21.50 / $215	$73.50 / $735	$37.50 / $375
100 users	$43 / $430	$147 / $1,470	$75 / $750
500 users	$52.50 / $525	$390.50 / $3,905	$230.50 / $2,305
1,000 users	$272.50 / $2,725	$655.50 / $6,555	$385.50 / $3,855

PocketQuery offers the lowest cost among the three options for every paid tier. At 100 users it is about 57% of the price of External Data for Confluence and roughly 29% of SQL for Confluence Pro. At 1,000 users PocketQuery is about 71% of External Data for Confluence and about 42% of SQL for Confluence Pro.

The three apps in detail

1. PocketQuery - SQL & REST for Confluence

Lively Apps: The app treats "where the data lives" as an entity called a Datasource - either a JDBC database or a REST API. The Marketplace listing names MySQL, PostgreSQL, MariaDB, MSSQL, Oracle, IBM DB2, IBM DB2 for i, SAP HANA, IBM Informix, Google BigQuery and Snowflake as supported SQL datasources, plus REST APIs with Basic Auth, OAuth 2.0 and custom headers. Query results render as tables, charts via a native Chart API, or templated dashboards built with Velocity, HTML and JavaScript. Result transformation runs inside a sandboxed JavaScript engine.

2. SQL for Confluence (Pro Edition)

Appfire: Formerly a Bob Swift app. The Marketplace listing names Microsoft SQL Server, PostgreSQL and MySQL, with AWS IAM authentication for AWS-hosted databases. Admins define profiles; users pick one in the macro editor and can preview SQL safely before publishing. Output is a dynamic table with sorting, filtering, row highlighting and pagination.

3. External Data for Confluence

codefortynine: The app's strength is source breadth: REST APIs with pagination, Salesforce, SharePoint, HubSpot, Oracle, IBM Db2, MSSQL, MySQL, PostgreSQL and Snowflake. It ships native bar, line and pie charts, a custom HTML template feature, and an explicit Convert data with JavaScript step.

Full comparison table

Dimension	PocketQuery (Lively Apps)	SQL for Confluence Pro (Appfire)	External Data for Confluence (codefortynine)
Installs (Atlassian Marketplace)	860	1,103	329
SQL data sources	MySQL, PostgreSQL, MariaDB, MSSQL, Oracle, IBM DB2, IBM DB2 for i, SAP HANA, IBM Informix, BigQuery, Snowflake	Microsoft SQL Server, PostgreSQL, MySQL	MySQL, PostgreSQL, Oracle, IBM Db2, MSSQL, Snowflake
Snowflake support	Yes, native	No	Yes, native
BigQuery support	Yes, native	No	Indirect (REST only)
Non-SQL data sources	REST APIs (Basic Auth, OAuth 2.0, custom headers)	None	REST APIs plus named connectors for Salesforce, SharePoint, HubSpot
Built-in diagram / chart engine	Yes, native Chart API	No, tables only	Yes, bar, line and pie charts
Templating	Yes, Velocity, HTML and JavaScript	No	Yes, custom HTML Template feature
Built-in result converter	Yes, sandboxed JavaScript engine plus column-level formatting (dates, numbers, currency)	No	Yes, JavaScript-based converter
Permission model (admin / spaces / users)	Admin-only Datasources; Queries restrictable to specific spaces; PocketQuery Admin and PocketQuery Editor role groups, independent of the Confluence site-admin group	Admin-driven profiles; per-data-source access; user permission settings	Admin-driven datasources; relies on Atlassian Confluence's own page and space permissions for end users
Security posture	Runs on Atlassian Forge; OAuth 2.0, Basic Auth and custom headers for REST Datasources; Datasource credentials never exposed to page authors	Profile-based access, per-data-source permission settings; AWS IAM for AWS-hosted DBs	OAuth 2.0 (Google, SharePoint, GitHub, Okta, Azure AD); admin-controlled datasources
Pricing, up to 10 users (mo / yr)	Free	Free	Free
Pricing, 25 users (mo / yr)	$10.75 / $107.50	$36.75 / $367.50	$18.75 / $187.50
Pricing, 50 users (mo / yr)	$21.50 / $215	$73.50 / $735	$37.50 / $375
Pricing, 100 users (mo / yr)	$43 / $430	$147 / $1,470	$75 / $750
Pricing, 500 users (mo / yr)	$52.50 / $525	$390.50 / $3,905	$230.50 / $2,305
Pricing, 1,000 users (mo / yr)	$272.50 / $2,725	$655.50 / $6,555	$385.50 / $3,855

What each app does well, and what holds it back

PocketQuery (Lively Apps)

What it does well. PocketQuery combines SQL and REST APIs in one app. It's the only option here with native support for both BigQuery and Snowflake, and the only one that names SAP HANA and IBM Db2 / Db2 for i. The Chart API, the Velocity / HTML / JavaScript template layer and the sandboxed JavaScript converter turn it from rows on a page into a light reporting tool inside Confluence. Running on Atlassian Forge keeps data inside Confluence, making security review faster. Admins own Datasources and credentials; Editors can author Queries against those Datasources; each Query can be restricted to specific Confluence spaces. The PocketQuery Admin role group is independent of the Confluence site-admin group, so your data team can own SQL governance without inheriting site-level admin rights. And on price, PocketQuery is the cheapest of the three at every paid tier, whether you bill monthly or annually.

What holds it back. The admin-controlled Datasource model supports governance but creates friction for analysts who want to write quick queries directly on a page. Teams that only need plain SQL against a single Postgres or MySQL may feel that the Datasource + Query model is more structure than they need.

SQL for Confluence (Pro Edition) (Appfire)

What it does well. The most institutionally mature option in the category. Long Marketplace history, Platinum Cloud Fortified trust signals, and an enterprise procurement process that's easy to navigate. The macro editor lets authors preview SQL safely before publishing. AWS IAM authentication is a nice touch for teams running their databases on AWS. The app fits neatly alongside the rest of Appfire's Confluence portfolio: Advanced Tables, Cache for Confluence, and so on.

What holds it back. No BigQuery, no Snowflake - which rules it out for warehouse-first teams in 2026. SQL only, with no REST and no SaaS connectors, so anything coming from Salesforce or HubSpot needs a second tool. No built-in chart engine, no templating, no result converter. Caching isn't a first-class feature either; Appfire effectively sells a second app, Cache for Confluence, to fill that gap, which is a real cost-of-ownership consideration. At every paid tier, this is the most expensive of the three.

External Data for Confluence (codefortynine)

What it does well. A broad set of source types named on the Marketplace listing: REST APIs with pagination, Salesforce, SharePoint, HubSpot, Oracle, IBM Db2, MSSQL, MySQL, PostgreSQL and Snowflake. Snowflake is a native SQL datasource. The app ships a chart engine, a custom HTML template feature and a JavaScript-based converter, so you can shape output before it hits the page. codefortynine is an Atlassian Platinum Marketplace Partner, Cloud Fortified, with a strong installed base across their portfolio.

What holds it back. Native warehouse coverage is narrower than PocketQuery's: BigQuery has to be reached through the REST API rather than a native driver, and Redshift, Databricks, ClickHouse, SAP HANA, MongoDB and IBM Db2 for i aren't listed as first-class targets. Pricing sits between PocketQuery (best price-to-feature ratio) and Appfire (most expensive) at every paid tier.

Evaluate each app yourself

The comparison table above has everything you need to match an app to your stack - and since all three offer a free tier for up to 10 users on the Atlassian Marketplace plus a 30-day trial at every higher tier, the fastest way to decide is to install each one against the data source you actually need to read and see how the macro behaves end-to-end.

👉 If you spot something in this article that doesn't match your experience with any of the three apps, let us know and we'll update the post.

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Get a three-month voucher for PocketQuery

Testing external queries in Confluence in just 30 days can be tough - we get it. If you'd like a three-month voucher for PocketQuery, just open a ticket in our help desk and we'll take care of it.