Windsor.ai vs Rivery: pricing, data sources, and a side-by-side test in Snowflake

✅ Flat plans from $19/mo. Rivery Base bills $0.90 per BDU credit, and every API sync costs at least 0.5 credits for each table it loads.

✅ 350+ data sources, against 200+ on Rivery.

✅ Same numbers in our Snowflake test. Windsor.ai loaded the same GA4 and Search Console numbers as Rivery, with dates stored as DATE columns.

✅ Claude and ChatGPT on every plan, and they can make changes in Meta Ads, Google Ads, TikTok Ads, LinkedIn Ads, and more.

✅ Free forever plan, no credit card.

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Windsor.ai vs Rivery: feature comparison

Feature

Windsor.ai

Rivery

Starting price

$19/moBasic, billed annually ($23 billed monthly): 3 data sources, 75 accounts, and 5 destination tasks

$0.90 per BDU credit on BasePay as you go. Professional, Pro Plus, and Enterprise prices come from sales

Pricing model

Tiered plansYour plan sets the number of sources and accounts. Runs are not counted. No plan has row or data volume limits, the free forever plan included. Your invoice is the plan price

Usage basedAPI sources cost 0.5 BDU credits per table per run, plus 0.5 for each extra 50 MB. Database and file sources cost 1 credit per 100 MB

Supported data sources

350+

200+

Warehouses and storage

✅ Snowflake, BigQuery, Redshift, Databricks, S3, Azure Blob, and moreOn every plan, including the free forever plan

✅ Snowflake, BigQuery, Redshift, Databricks, S3, and Azure BlobPlus Azure Synapse, Firebolt, Google Cloud Storage, and Athena

BI tools and spreadsheets

✅ Google Sheets, Data Studio, Excel, Power BI, and moreTableau via Google Sheets

No direct destinationIts target list has warehouses, databases, storage, and email, but no spreadsheets or BI tools

Transformations

Field selection, filters, and custom metricsWindsor.ai’s ELT page lists no SQL or Python steps and no orchestration between tasks

✅ SQL on every editionPython from Professional, and workflow orchestration from Base

Database replication

PostgreSQL, MySQL, MongoDB, and Supabase source connectorsNo log-based change data capture

✅ Database sources and log-based change data capture

Sending warehouse data to business apps (reverse ETL)

PartlyNo dedicated reverse ETL tool. BigQuery, Snowflake, and Redshift can be sources, so warehouse tables can go to Google Sheets or Airtable on a schedule. Claude and ChatGPT can make changes in ad platforms with write actions. For syncing tables into a CRM, our ETL and ELT guide names Census and Hightouch

✅ Reverse ETLOn every edition, Base included. Rivery’s product page names Salesforce and HubSpot

Claude and ChatGPT

✅ Listed in Claude’s connector directory and ChatGPT’s plugin directoryEvery plan, including the free forever plan

A Claude plugin (Boomi Companion)For Claude Code and Claude Cowork. It helps you build and fix data flows. It does not answer questions from your marketing data

Write actions from Claude or ChatGPT

✅ Meta Ads, Google Ads, TikTok Ads, LinkedIn Ads, Microsoft Ads, and moreSee the full list of write actions

None in ad platforms

Fastest scheduled sync to warehouses and Sheets

Daily on Basic, hourly from Standard, every 15 minutes on ProfessionalIncremental scheduled syncs are supported where the connector and source setup allow it

Every 60 minutes on Base15 on Professional and Pro Plus, 5 on Enterprise

Users

✅ Unlimited on every paid plan

2 on BaseUnlimited on Professional, Pro Plus, and Enterprise

Free plan

✅ Free forever plan, no credit card1 user, 1 source, 1 account, and 30 days of history

Trial of 14 days or 1,000 creditsWhichever expires first. No free plan after that

Windsor.ai vs Rivery: what three common setups cost

Solo marketer

GA4, Search Console, and Google Ads
One account each
Daily syncs to Snowflake

You choose...

Windsor.ai

The Basic plan covers it for $19/mo billed annually ($23 billed monthly).

Rivery

About $40.50/mo on Base at the monthly billing rate: 0.5 credits for each of the 3 tables on each daily run. Warehouse compute is extra with both tools.

Key benefit

Add up to 72 more accounts on the same platforms (75 minus 3) without changing plan.

Marketing agency

Google Ads, Meta Ads, and GA4
40 client accounts across the three platforms
Hourly syncs to BigQuery

You choose...

Windsor.ai

Standard covers 7 sources and 75 accounts with hourly scheduled syncs to warehouses and Sheets for $99/mo billed annually ($118 billed monthly).

Rivery

At least $972/mo on Base, with one table per platform and every client account for that platform in the same table: 0.5 credits per table on each of 720 hourly runs a month. Each extra 50 MB in a run adds 0.5 credits.

Key benefit

Add 35 more client accounts (75 minus 40) at the same price.

Data team replicating a database

A PostgreSQL production database
About 5,000 MB of new data a month into Snowflake
SQL transformations and scheduled workflows after each load

You choose...

Windsor.ai

Windsor.ai has no log-based change data capture, no SQL steps after each load, and no workflow orchestration.

Rivery

About $45/mo on Base for 5,000 MB a month without log-based change data capture (1 credit per 100 MB), and about $90/mo with it (2 credits per 100 MB). Boomi bills database volume pro rata, whatever the number of runs. Log-based change data capture, SQL transformations, and workflow orchestration come with every edition, Base included.

Key benefit

Keep your marketing sources on Windsor.ai, and send them to the Snowflake database Rivery loads into.

Windsor.ai and Rivery side by side in Snowflake

We ran the test in one Snowflake account on 30 October 2026. Each tool loaded the same data for 1 to 28 October 2026 into its own schema:

GA4 sessions by day, channel, and source
Search Console clicks by day

Both tools signed in as the same Snowflake service user with a key pair.

Windsor.ai ran on our Enterprise plan, and Rivery on its 14-day trial. This was our first time building flows in Rivery. Rivery’s setup times include learning the interface.

Test 1: Do the GA4 numbers match?

We added up sessions and engaged sessions for two weeks and worked out the bounce rate from each tool’s table.

Both tools returned the same numbers for both weeks (one row per day, channel, and source):

14 to 20 October: 58 rows, 1,093 sessions, and a 78.59% bounce rate
21 to 27 October: 53 rows, 1,055 sessions, and a 76.97% bounce rate

Both tools load GA4’s figures by day. On 29 October we compared them with GA4’s own weekly report:

21 to 27 October: GA4 showed the same 1,055 sessions and a 77.0% bounce rate, the same rate rounded.
14 to 20 October: GA4 showed 1,097 sessions and a 78.7% bounce rate. GA4’s weekly total was 4 sessions more than the sum of its days.

Snowflake query result with one row per week and tool: Rivery and Windsor.ai both show 58 rows, 1,093 sessions, 234 engaged sessions, and a 78.59% bounce rate for 14 to 20 October 2026, and 53 rows, 1,055 sessions, 243 engaged sessions, and 76.97% for 21 to 27 October. Captured 30 October 2026.

Test 2: Joining Search Console and GA4 in SQL

We joined each tool’s Search Console clicks to its GA4 sessions from Google organic search, day by day, and flagged days where clicks and sessions differed by more than 20% of sessions.

Both tools returned the same clicks and sessions on every day from 1 to 28 October. The gap was more than 20% of sessions on three days: 7 October (30.9%), 11 October (32.8%), and 20 October (37.5%, 77 clicks against 56 sessions).

Windsor.ai stored the date as a DATE in both tables. Rivery’s Auto Mapping stored the GA4 date as a number (20261014) and the Search Console date as text. You can change a column’s type or cast it with an SQL expression in Rivery’s column mapping. We kept the defaults. Each join needed a conversion to DATE first. Rivery stored sessions and clicks as whole numbers (NUMBER), and Windsor.ai as decimals (FLOAT).

Snowflake query result for 1 to 28 October 2026 with clicks, Google organic sessions, and the gap as a percentage of sessions for Windsor.ai and Rivery side by side. The two tools show the same values on every day. The gap is more than 20% of sessions on 7 October (30.9%), 11 October (32.8%), and 20 October (37.5%). Captured 3 November 2026.

Test 3: Setup, reload, and cost

We timed each GA4 setup, ran each GA4 load a second time, and checked for duplicate rows and cost.

Windsor.ai setup: about 7 minutes from a ready Snowflake key to the start of the Snowflake load for the GA4 task, including the key upload. We uploaded the key file twice, because each new task needs its own upload.
Rivery setup: about 12 minutes from a saved Snowflake connection to the start of the Snowflake load for the GA4 flow: 11 minutes of setup and 44 seconds from the GA4 pull to the start of the load. Picking Snowflake as the target cleared the dates and table name we had entered, and the default Upsert-Merge mode needed key columns picked by hand. Rivery saves the Snowflake connection once and reuses it.
Second flow: Rivery’s Search Console flow took 2 minutes to set up and 49 seconds from the pull to the start of the load. This time we picked the target before entering the dates. Rivery kept everything we entered. We did not time Windsor.ai’s second task.
Columns: Windsor.ai loaded only the fields we picked. Rivery added GA4 account and property names, and Search Console CTR and position, by default.
Second run: neither tool created duplicates. Windsor.ai reloaded the fixed 1 to 28 October range we set in its task. We did not test incremental loading on Windsor.ai. Rivery’s GA4 flow loads incrementally: the second run moved the start date forward and added 29 and 30 October (11 rows).
Cost: each Rivery run used 0.5 credits. Our three runs used 1.5 credits, $1.35 at the Base rate. A daily sync of these two tables would use 30 credits a month, about $27/mo. On Windsor.ai, the two sources fit in Basic at $19/mo billed annually ($23 billed monthly).

Rivery Activities page for 30 October 2026: 3 successful runs and 1.5 BDU in total, 1 BDU for the GA4 flow (2 runs) and 0.5 for the Search Console flow (1 run). Captured 30 October 2026.

Windsor.ai Destinations Overview with the two daily Snowflake tasks used in the test, last updated 30 October 2026. The site name and email are blurred. Captured 30 October 2026.

How G2 reviewers rate Windsor.ai and Rivery

Meets Requirements: Windsor.ai 8.8, Rivery 9.3
Ease of Use: Windsor.ai 8.2, Rivery 9.5
Ease of Setup: Windsor.ai 8.1, Rivery 9.2
Ease of Admin: Windsor.ai 8.6, Rivery 9.1
Quality of Support: Windsor.ai 8.9, Rivery 9.4
Good Partner in Doing Business: Windsor.ai 9.2, Rivery 9.6
Product Direction: Windsor.ai 9.2, Rivery 9.3

Rivery has 4.7 stars from 121 G2 reviews, and Windsor.ai has 4.4 from 90. G2 lists Rivery as Boomi Data Integration. G2 reviewers rate Rivery higher in all seven categories. Reviewers report a return on investment after 6 months with Windsor.ai and 9 months with Rivery, from 12 and 8 responses. They report implementation in under 1 month with Rivery and 1 month with Windsor.ai, from 14 and 16 responses.

See the G2 comparison of Rivery and Windsor.ai

G2 comparison page, checked 30 October 2026.

Windsor is trusted by 25,000+ global businesses of all sizes and industries

About Windsor.ai

Windsor.ai has no-code connectors that pull data from marketing, sales, CRM, e-commerce, and accounting apps. You can send that data to Claude, ChatGPT, spreadsheets, BI tools, and data warehouses, and schedule syncs to keep warehouses and Sheets up to date.

About this comparison

Windsor.ai publishes this page, and we sell one of the two tools compared here. Our team uses Windsor.ai daily. Your first setup may take longer than ours. On 30 October 2026, we ran the tests above on one GA4 property and its Search Console site, with both tools loading into one Snowflake account. The same day, we checked G2’s comparison page, both pricing pages (windsor.ai/pricing and rivery.io/pricing), and Boomi’s pricing FAQ. Check both pricing pages again before you buy, because plans change.

Rivery is now Boomi Data Integration. Boomi bought Rivery in December 2024, and the product is still at rivery.io and console.rivery.io.