[PaaS only]{class="badge informative" title="Applies to Adobe Commerce on Cloud projects (Adobe-managed PaaS infrastructure) and on-premises projects only."}

Estimate data volume and sync time

Adobe recommends estimating data volume and sync time before starting any feed synchronization to ensure smooth scheduling and avoid disruptions in site operations. This is especially important when planning initial syncs or large-scale catalog updates, such as mass price changes.

By default, the connector processes feeds in single-thread mode. There is no parallelization of the feed submission process. The ingestion API accepts up to 2 requests per second. However, the base allocation for the Adobe Commerce Optimizer ingestion rate limits throughput to the following:

  • Up to 1,000 products per minute (a product is a SKU with attributes in a specific store view). See Limits and boundaries for base allocation details.
  • Up to 50,000 prices per minute

Factors that affect sync time

The estimates below assume the following conditions:

  • Thread count: 1 (default)
  • Feed acceptance rate: 2 requests per second (0.5 seconds per request)
  • All products are assigned to all existing websites

Actual transmission speed varies depending on request payload size and the current load on the Commerce application server.

Calculate sync time per feed

Use the following table to estimate the number of records, requests, and sync time for each connector feed. Batch size values reflect the limits defined in the supported feeds reference.

NOTE
Product sync time is based on the base allocation limit of 1,000 products per minute. For other feeds, calculations are based on a transmission rate of 2 requests per second. Actual speed depends on payload size and server load.
The prices estimate assumes all customer groups have unique prices.
Feed
Data example
Formula
Predicted requests
Predicted sync time
Products
Products (P): 10,000, Store Views (SV): 4
P × SV = 40,000 records
40,000 ÷ batch size (100) = 400
40,000 ÷ 1,000 records/min = 40 min
Categories
Categories ©: 500, Store Views (SV): 4
C × SV = 2,000 records
2,000 ÷ batch size (100) = 20
(20 × 0.5 s) ÷ 60 = ~10 s
Product attributes
Attributes (A): 200, Store Views (SV): 4
A × SV = 800 records
800 ÷ batch size (100) = 8
(8 × 0.5 s) ÷ 60 = ~4 s
Prices
Products (P): 10,000, Websites (WS): 2, Customer Groups (CG): 6
P × WS × CG = 120,000 records
120,000 ÷ batch size (500) = 240
(240 × 0.5 s) ÷ 60 = 2 min
Price books
Websites (WS): 2, Customer Groups (CG): 6
WS × CG = 12 records
12 ÷ batch size (500) = 1
(1 × 0.5 s) ÷ 60 = < 1 s
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