1,000 Products (No Images)

June 25, 2026

WP All Import Pro imported 1,000 WooCommerce products in 3 minutes 48 seconds on a 4-vCPU server with no images. The same feed, on the same machine, took Super Speedy Imports about 9 seconds — roughly 24× faster. Full timings, dataset and a reproduce bundle are below.

Summary

  • WP All Import Pro result: 3m 48s (228s) for 1,000 products, ~4.4 products/sec.
  • Scenario: 1,000 simple + variable WooCommerce products, no images, fresh import.
  • Compared with: Super Speedy Imports — ~9s (~24× faster) on identical hardware and data.
  • Version tested: WP All Import Pro 5.0.6 + WooCommerce add-on 4.0.6 (defaults).
  • Reproducible: full dataset + the exact WP All Import template linked below.

Results

MetricWP All Import ProSSISSI + SPRO
Total time3m 48s (228s)~9s~10s
Records / sec~4.4~105~95
Time per product~0.23s~0.009s~0.011s
Speed vs WP All Import~24× faster~23× faster

Where the time goes

WP All Import Pro processes a feed row-by-row in a single PHP process, running its mapping and WooCommerce save logic per product. At 1,000 rows that’s ~0.23s per product. It’s a robust, general-purpose importer — but the per-row model is what sets the floor here, and that per-row cost grows as the catalogue grows (see the 50,000-product benchmarks).

Key findings

  • At small scale the gap is at its narrowest — ~24×. This is the conservative end; larger catalogues widen it dramatically.
  • WP All Import produced a correct catalogue; the difference is purely time.

Compare: the same test from Super Speedy Imports’ side — Super Speedy Imports: 1,000 products (no images) — or read the full Super Speedy Imports vs WP All Import Pro comparison.

Methodology

Environment

  • Server: Hetzner CPX32 — 4 vCPU (AMD), 8 GB RAM, 160 GB SSD, Ubuntu 24.04 LTS.
  • Stack: WooCommerce 10.3, PHP 8.2, MariaDB 10.6, WordPress 7.0.
  • Plugins: WP All Import Pro 5.0.6 + WooCommerce add-on 4.0.6 (defaults, single process); Super Speedy Imports 2.55.7 (8 workers) for comparison.

Test setup

  • Source: single CSV, 1,000 rows.
  • WP All Import: default settings, run via wp all-import run <id>.
  • State: fresh import into an empty WooCommerce catalogue; snapshot-reset between runs.
  • Images: none in this scenario.

Rules & measurement

  • Same input file, same hardware, same scope, same expected end-state (1,000 products) for both plugins.
  • Headline figure is total wall-clock duration; records/sec and time-per-product are derived from it.

This is not intended as a universal benchmark — your data shape, hardware and hosting will differ. It is one carefully controlled, fully reproducible scenario.

Dataset

  • Products: 1,000 (mix of simple and variable).
  • Taxonomies: product_cat, product_brand, plus variation attributes pa_color and pa_size.
  • Metadata: SKU, regular/sale price, weight.
  • Images: none.

Reproduce

Everything needed to repeat this run is in the bundle below, including the exact WP All Import Pro template we used.

  • Download: wpai-benchmark-1000-products.zip
  • Contains: shirt-test-1000.csv, wpai-template-export.json, taxonomies.json, the SSI config (for comparison), results-wpai.json / results-ssi.json, and a HOW-TO-REPRODUCE.md.

Steps (WP All Import Pro)

  1. wp-admin → All Import → New Import, upload shirt-test-1000.csv.
  2. Map columns to WooCommerce fields — or import wpai-template-export.json if your version supports it (it’s the exact template we used).
  3. Run for a clean timing: time wp all-import run <id>.

If your results differ significantly, tell us — we’d like to know.

FAQ

Is this a fair test of WP All Import?

We used WP All Import Pro’s default settings and a clean run on the same server and feed. It produced the correct 1,000-product catalogue. We publish the full template and dataset so you can verify it yourself.

Were images included?

No — this scenario isolates the database and product-build work. See the 50,000-product (with images) benchmark for image handling, where the gap is much larger.

Can I reproduce this locally?

Yes — download the bundle above. Times vary with hardware, but the relative difference should hold.

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