What Keepa Is Known For
Keepa is an Amazon-focused price history service, strongest when you need long Amazon price and rank history for one marketplace. kwery is a multi-source API: 12 marketplaces returned in one normalized schema with per-record provenance, trust scoring and change events, so it fits teams whose pricing decisions span more than Amazon.
A deep Amazon-specific dataset known for long-term price and rank history, tracking and Amazon-native product intelligence.
Long-Term Amazon History
Extensive retained price, rank and offer history for Amazon products across marketplaces.
Tracking and Alerts
Product tracking with threshold-based notifications built around the Amazon catalog.
Amazon-Native Model
Data is organized around ASINs and Amazon-specific concepts, including Buy Box and seller history.
Analysis Depth
A widely used reference dataset for Amazon seller and category analysis.
Where the Products Overlap
A fair comparison starts with the shared ground. Both products are used for the following, which is why they appear in the same evaluation at all. Below the shared band, the ledger shows where the two designs diverge.
Where they overlap
Where they diverge
Amazon coverage
Deep, built around ASINs, with years of stored history
Current prices read directly, with sellers and offers included
Historical depth
Core strength, years of retained series
History builds up from your first reading onward
Other marketplaces
None, Amazon only
Google Shopping, Idealo, eBay, Walmart, Otto, Kaufland and further sources
Finding the right product
You supply the ASIN; Amazon-only catalogue lookup
Give a barcode (GTIN/EAN), ASIN or marketplace ID and get the matching product on that marketplace, with a match confidence
Same fields across sources
Amazon-specific field names only
The same response format for every source
Amazon coverage
Keepa
Deep, built around ASINs, with years of stored history
kwery
Current prices read directly, with sellers and offers included
Historical depth
Keepa
Core strength, years of retained series
kwery
History builds up from your first reading onward
Other marketplaces
Keepa
None, Amazon only
kwery
Google Shopping, Idealo, eBay, Walmart, Otto, Kaufland and further sources
Finding the right product
Keepa
You supply the ASIN; Amazon-only catalogue lookup
kwery
Give a barcode (GTIN/EAN), ASIN or marketplace ID and get the matching product on that marketplace, with a match confidence
Same fields across sources
Keepa
Amazon-specific field names only
kwery
The same response format for every source
Deep Amazon History or Current Multi-Marketplace Data?
Keepa's centre of gravity is the retained time series. The value is in what a product has done over months and years, which is difficult and expensive to reconstruct once you decide you need it, and Amazon is the domain it models in depth.
kwery's centre of gravity is the current reading and the context around it: which product it matched, how complete the offer set is, whether the value can be trusted, where and when it was collected, and what changed since the last reading.
Because kwery detects change by comparing one reading with the last one rather than keeping a general archive, teams that need deep Amazon backfill and teams that need trustworthy current inputs across marketplaces are usually asking different questions, and sometimes run both.
Architecture
Years of history ←→ Current prices
Keepa
Amazon time series, retained and queryable
kwery
Current prices across marketplaces
Both paths deliver marketplace data. They differ in what your application receives and what it still has to model.
If the underlying layers are still unclear, the marketplace data infrastructure guide describes what sits between a marketplace and a production record.
How Keepa and kwery Compare
Each row is either a shared capability, a genuine strength of the other product, or a kwery capability the other product does not document. Verify every row against current documentation during evaluation.
- 01
Amazon coverage
Keepa
Deep, built around ASINs, with years of stored history
kwery
Current prices read directly, with sellers and offers included
- 02
Historical depth
Keepa
Core strength, years of retained series
kwery
History builds up from your first reading onward
- 03
Other marketplaces
Keepa
None, Amazon only
kwery
Google Shopping, Idealo, eBay, Walmart, Otto, Kaufland and further sources
- 04
Finding the right product
Keepa
You supply the ASIN; Amazon-only catalogue lookup
kwery
Give a barcode (GTIN/EAN), ASIN or marketplace ID and get the matching product on that marketplace, with a match confidence
- 05
Same fields across sources
Keepa
Amazon-specific field names only
kwery
The same response format for every source
- 06
Can you trust the data?
Keepa
Not offered, the response carries the data, not a confidence signal
kwery
A trust score and data-health flags come back with every record
- 07
Where the data came from
Keepa
Timestamps only, no source, country or collection details
kwery
Every record says which source, which country, how it was collected and when
- 08
What changed since last time
Keepa
Tracking and threshold alerts within Amazon
kwery
A structured change record when the next reading differs from the previous one across sources
- 09
How the data reaches your system
Keepa
API and platform access oriented to analysis and tracking
kwery
Synchronous single lookups (wait), batch jobs and webhooks designed for machine-to-machine use
- 10
Pricing model
Keepa
Token-based; verify how history depth affects consumption
kwery
One credit per complete SKU dataset: one SKU, one source, fetched fresh. Matching the product, the product data and the offers are all included.
| Dimension | Keepa | kwery |
|---|---|---|
| Amazon coverage | Deep, built around ASINs, with years of stored history | Current prices read directly, with sellers and offers included |
| Historical depth | Core strength, years of retained series | History builds up from your first reading onward |
| Other marketplaces | None, Amazon only | Google Shopping, Idealo, eBay, Walmart, Otto, Kaufland and further sources |
| Finding the right product | You supply the ASIN; Amazon-only catalogue lookup | Give a barcode (GTIN/EAN), ASIN or marketplace ID and get the matching product on that marketplace, with a match confidence |
| Same fields across sources | Amazon-specific field names only | The same response format for every source |
| Can you trust the data? | Not offered, the response carries the data, not a confidence signal | A trust score and data-health flags come back with every record |
| Where the data came from | Timestamps only, no source, country or collection details | Every record says which source, which country, how it was collected and when |
| What changed since last time | Tracking and threshold alerts within Amazon | A structured change record when the next reading differs from the previous one across sources |
| How the data reaches your system | API and platform access oriented to analysis and tracking | Synchronous single lookups (wait), batch jobs and webhooks designed for machine-to-machine use |
| Pricing model | Token-based; verify how history depth affects consumption | One credit per complete SKU dataset: one SKU, one source, fetched fresh. Matching the product, the product data and the offers are all included. |
Verify each row against current documentation during evaluation. Last verified: September 2026.
What Comes Back With Each Record
Both products return prices and offers. The rows below show what else is attached to a record when it reaches your system, and which side provides it.
Coverage
Which marketplaces can I read?
BothKeepa
Amazon only, 1 source across 11 marketplaces
kwery
Amazon, Google Shopping, Idealo, eBay, Walmart, Otto, Kaufland and further supported sources
Amazon only, 1 source across 11 marketplaces
Amazon, Google Shopping, Idealo, eBay, Walmart, Otto, Kaufland and further supported sources
Collection
Who runs the retrieval?
BothKeepa
Managed retrieval and continuous Amazon tracking
kwery
Managed retrieval from the requested marketplace
Managed retrieval and continuous Amazon tracking
Managed retrieval from the requested marketplace
Product matching
Is this the right product?
BothKeepa
ASIN lookup
kwery
Give a barcode (GTIN/EAN), ASIN or marketplace ID and get the matching product on that marketplace, with a match confidence
ASIN lookup
Give a barcode (GTIN/EAN), ASIN or marketplace ID and get the matching product on that marketplace, with a match confidence
Response format
Does one integration read every source?
kwery onlyKeepa
Amazon-specific field names only
kwery
The same response format for every source
Amazon-specific field names only
The same response format for every source
Can you trust the data?
Should my system act on this price?
kwery onlyKeepa
Not offered, the response carries the data, not a confidence signal
kwery
A trust score and data-health flags come back with every record
Not offered, the response carries the data, not a confidence signal
A trust score and data-health flags come back with every record
Where the data came from
Can I see where and when this was collected?
kwery onlyKeepa
Timestamped history arrays; no per-record source or collection details
kwery
Every record says which source, which country, how it was collected and when
Timestamped history arrays; no per-record source or collection details
Every record says which source, which country, how it was collected and when
What changed since last time
What changed since the last reading?
BothKeepa
Tracking and threshold alerts within Amazon; tracked products consume the plan's token refill
kwery
A structured change record when the next reading differs from the previous one
Tracking and threshold alerts within Amazon; tracked products consume the plan's token refill
A structured change record when the next reading differs from the previous one
Freshness
How current is the record I paid for?
kwery onlyKeepa
One token returns a stored record up to an hour old; live offers are charged at six tokens per ten offers
kwery
Every credit is a fresh fetch from the requested source at request time
One token returns a stored record up to an hour old; live offers are charged at six tokens per ten offers
Every credit is a fresh fetch from the requested source at request time
Application layer
Where does the pricing logic live?
Keepa onlyKeepa
Charts, deal finder and tracking interface
kwery
None, the pricing logic stays in your systems
Charts, deal finder and tracking interface
None, the pricing logic stays in your systems
History depth
Can I read years of past prices?
Keepa onlyKeepa
Years of retained Amazon price, rank and offer history
kwery
History builds up from your first reading onward
Years of retained Amazon price, rank and offer history
History builds up from your first reading onward
Design emphasis, not quality ranking
How Price and Offer Changes Are Detected
kwery discovers a change when the next reading differs from the previous one and sends a structured change record through the configured delivery workflow, a real difference between two readings, not a platform alert.
Keepa stores timestamped history arrays and offers product tracking, but every tracked product permanently consumes part of the account's token refill rate, so change coverage is bounded by plan tokens rather than by the size of the catalogue.
Detected Change Event
- Observation T1€129,90
- Marketplace changesunknown
- Observation T2€119,90
kwery detects
€129,90 → €119,90
kwery discovers a change when the next marketplace observation differs from the previous one. It does not know the exact instant the marketplace changed. The structured delta is then emitted through the configured delivery workflow.
Compare Cost per Usable Dataset, Not Cost per Credit
The comparable figure is what each side charges for one complete SKU dataset.
How we compare cost per datasetKeepa’s unit
Variable6+
tokens per complete SKU dataset (live offers)
- Cached record1 token, up to an hour old
- Live offers6 tokens per 10 offers
- TrackingConsumes the plan's token refill
- Coverage1 source (Amazon) · 11 marketplaces
kwery’s unit
Fixed1
credit per complete SKU dataset, everything included
- 1 creditper SKU × source × fresh fetch
- Includedmatching, product data and offers
- Cache hitsno additional credit
- Rolloverunused paid credits while active
On Amazon, Walmart and eBay, one kwery credit covers 2 complete SKU datasets (search + product + offers, matched, each). All other sources: one credit, one complete SKU dataset.
Billing unit
- Keepa
- Access is token-based. One token returns a stored database record that may be up to an hour old; live offer data is charged separately, at six tokens per ten offers.
- kwery
- One credit per complete SKU dataset: one SKU, one source, fetched fresh. Matching the product, the product data and the offers are all included.
Years of history and current prices are different products. Compare each against the requirement it serves rather than against each other.
kwery charges one unit for one complete SKU dataset: no separate matching step, no separate lookup, no per-endpoint stacking, so the cost of an integration can be calculated before it is built.
What One Complete Dataset Costs
The steps below are drawn from publicly available documentation and should be verified against current documentation during evaluation.
Find the product
Keepa
ASIN lookup, or a barcode resolved against Keepa's Amazon catalog
kwery
Included, barcode, ASIN or marketplace ID matched in the same call
Find the product
ASIN lookup, or a barcode resolved against Keepa's Amazon catalog
Included, barcode, ASIN or marketplace ID matched in the same call
Product data
Keepa
1 token for the stored record, which may be up to an hour old
kwery
Included in the same call, fetched fresh
Product data
1 token for the stored record, which may be up to an hour old
Included in the same call, fetched fresh
Live offers
Keepa
6 tokens per 10 offers when current offer data is required
kwery
Included in the same call
Live offers
6 tokens per 10 offers when current offer data is required
Included in the same call
Continuous refresh
Keepa
Tracked products draw on the plan's token refill rate
kwery
One credit per complete SKU dataset, with optional webhook delivery; On Amazon, Walmart and eBay, one credit covers 2 complete SKU datasets (search + product + offers, matched, each).
Continuous refresh
Tracked products draw on the plan's token refill rate
One credit per complete SKU dataset, with optional webhook delivery; On Amazon, Walmart and eBay, one credit covers 2 complete SKU datasets (search + product + offers, matched, each).
One complete SKU dataset
Keepa
6+ tokens
kwery
1 credit
One complete SKU dataset
6+ tokens
1 credit
The one-token figure often quoted refers to a stored record rather than a live one. For a live offer set the cost scales with the number of offers, which puts a full live dataset in a comparable range to a fresh crawl rather than an order of magnitude below it. Keepa covers a single source, Amazon, across 11 marketplaces. kwery covers 12 marketplaces, including 22 Amazon marketplaces. Keepa's published terms also require written consent before their data is redistributed to third parties, so teams planning to pass data onward should confirm the current terms with Keepa first. Token costs should be verified against current Keepa documentation.
When Keepa or kwery Is the Better Fit
Neither option is the general answer. The requirement decides, and the requirement is usually clearer than the feature comparison.
Keepa may fit better when
- long Amazon history is central to the product or analysis
- the work is Amazon-only and ASIN-centred
- seasonality, rank movement or long-run trends drive the decision
- an hour-old stored record is fresh enough for the decision
- researchers and analysts are the primary consumers
kwery may fit better when
- the system prices against several marketplaces, not only Amazon
- current, trustworthy prices matter more than deep history
- freshness must be guaranteed at the moment of the request
- automated logic needs data-health flags before acting
- you need change records delivered into a production pipeline
Before You Switch
A provider migration is not only an API-key change. These considerations are specific to moving between Keepa and kwery:
History Retention
Decide where existing Amazon history should live. kwery builds history from the first reading onward rather than backfilling an archive.
Map to Your Catalog Keys
kwery matches the right product within each requested source but does not link the same product across marketplaces. When several sources feed one model, map each source's record to your own catalogue keys.
Alerts to Detected Change
Threshold alerts become structured change records your system evaluates, which keeps pricing rules inside your application.
General migration checklist
- Identifier Compatibility
- Can existing GTINs, EANs, UPCs, ASINs or source URLs be reused as request inputs?
- Schema Migration
- Which fields change name, type or meaning, and which consumers read them today?
- Source Parity
- Are all required marketplaces and countries available on both sides of the move?
- Freshness Semantics
- Does "fresh" mean the same thing in both systems, and does every record carry a collection timestamp?
- Offer Modeling
- Are seller, shipping and availability represented in equivalent ways?
- History
- Will historical records need to remain in the existing system, and for how long?
- Failure Handling
- How should the application interpret unresolved products and partial results?
- Billing Unit
- Are you paying by request, credit, record, product/source lookup or another unit?