Auto Parts (US), 4th Edition
US market car parts database up to year 2015
↑Data Structure
brand
[765]
bigint(20) unsigned
+id
(100%)
timestamp
+ts
(100%)
varchar(255)
+title
(100%)
varchar(255)
+slug
(100%)
char(1)
+initial
(100%)
category
[8]
bigint(20) unsigned
+id
(100%)
timestamp
+ts
(100%)
varchar(255)
+title
(100%)
varchar(255)
+slug
(100%)
category_sub
[158]
bigint(20) unsigned
+id
(100%)
timestamp
+ts
(100%)
varchar(255)
+title
(100%)
varchar(255)
+slug
(100%)
bigint(20) unsigned
+category_id
(100%)
category_sub_sub
[1,540]
bigint(20) unsigned
+id
(100%)
timestamp
+ts
(100%)
varchar(255)
+title
(100%)
varchar(255)
+slug
(100%)
bigint(20) unsigned
+category_sub_id
(100%)
engine
[74,205]
bigint(20) unsigned
+id
(100%)
timestamp
+ts
(100%)
varchar(255)
+title
(100%)
bigint(20) unsigned
+submodel_id
(100%)
varchar(255)
+make
(100%)
char(4)
+year
(100%)
varchar(255)
+model
(100%)
varchar(255)
+submodel
(100%)
int(10) unsigned
+num_parts
(97.5%)
engine2part
[117,229,740]
bigint(20) unsigned
+id
(100%)
timestamp
+ts
(100%)
bigint(20) unsigned
+part_id
(100%)
bigint(20) unsigned
+engine_id
(100%)
make
[68]
bigint(20) unsigned
+id
(100%)
timestamp
+ts
(100%)
varchar(255)
+title
(100%)
int(10) unsigned
+num_parts
(100%)
make2year
[2,978]
bigint(20) unsigned
+id
(100%)
timestamp
+ts
(100%)
varchar(255)
+make
(100%)
bigint(20) unsigned
+make_id
(100%)
char(4)
+year
(100%)
model
[22,603]
bigint(20) unsigned
+id
(100%)
timestamp
+ts
(100%)
varchar(255)
+title
(100%)
bigint(20) unsigned
+make2year_id
(100%)
varchar(255)
+make
(100%)
char(4)
+year
(100%)
part
[1,708,530]
bigint(20) unsigned
+id
(100%)
timestamp
+ts
(100%)
varchar(255)
+title
(100%)
varchar(255)
+part_number
(100%)
varchar(255)
+manufacturer_number
(100%)
varchar(255)
+list_price
(100%)
tinyint(1)
+universal_part
(1.8%)
varchar(255)
+brand_title
(71.1%)
bigint(20) unsigned
+brand_id
(71.1%)
mediumtext
+description
(100%)
text
+fits
(97.5%)
text
+specifications_json
(100%)
varchar(255)
+Quantity_Sold
(97.5%)
varchar(255)
+Product_Fit
(90.5%)
varchar(255)
+Warranty
(82.9%)
varchar(255)
+Color_Finish
(72.8%)
varchar(255)
+Material
(72.1%)
varchar(255)
+Location
(66.2%)
varchar(255)
+Series
(57.7%)
text
+Notes
(47.4%)
varchar(255)
+Seat_Type
(44.7%)
text
+Fit_Note
(43.9%)
varchar(255)
+Design
(43.8%)
varchar(255)
+Position
(38.5%)
varchar(255)
+Type
(20.8%)
varchar(255)
+Row
(19.1%)
varchar(255)
+Recommended_Use
(13%)
varchar(255)
+Vehicle_Body_Type
(7.8%)
varchar(255)
+Construction
(7.5%)
varchar(255)
+Kit_Type
(6.7%)
submodel
[43,921]
bigint(20) unsigned
+id
(100%)
timestamp
+ts
(100%)
varchar(255)
+title
(100%)
bigint(20) unsigned
+model_id
(100%)
varchar(255)
+make
(100%)
char(4)
+year
(100%)
varchar(255)
+model
(100%)
year
[74]
bigint(20) unsigned
+id
(100%)
timestamp
+ts
(100%)
char(4)
+title
(100%)
int(10) unsigned
+num_parts
(100%)
↑Description
This is the 4th edition of The Data Planet Auto Parts Database for the US automobile market with car makes, models, sub-models, engines and trims up to year 2015. It's in every way better than the 3rd edition but lacks association between the parts and the categories.
↑Data Profile
| Size | 18.21G |
| Tables | 12 |
| Last Commit | 2017-04-20 01:49:42 |
↑Updates / Commits
| Time | Size | Tables | Columns | Rows |
|---|---|---|---|---|
| 2017-04-20 01:49:42 | 18.21G | 12 | 88 | 119084590 |
| 2016-08-09 20:25:30 | 18.21G | 12 | 88 | 119084590 |
↑Pricing
All prices are in Datactory Credits.
| Table | Rows | Price per Row (Credits) | Subtotal (Credits) |
|---|---|---|---|
| brand | 765 | .001 | 0.765 |
| category | 8 | .001 | 0.008 |
| category_sub | 158 | .001 | 0.158 |
| category_sub_sub | 1,540 | .001 | 1.54 |
| engine | 74,205 | .001 | 74.205 |
| engine2part | 117,229,740 | .001 | 117229.74 |
| make | 68 | .001 | 0.068 |
| make2year | 2,978 | .001 | 2.978 |
| model | 22,603 | .001 | 22.603 |
| part | 1,708,530 | .001 | 1708.53 |
| submodel | 43,921 | .001 | 43.921 |
| year | 74 | .001 | 0.074 |
| Total Credits | 119084.59 Credits (1) (2) | ||
|
(1). Plus cost by query time at 0.1 credits per second. A typical query takes about 0.001 seconds which would then charge you 0.0001 credits.
(2). This is the total amount of credits required for ALL rows in these tables. You are free to query for only a selected part of them, even a single row, and pay only for that. |
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↑How to Access
Click to see how to access this dataset.