Building Products Data Provider · Head-to-head
CelesTrak Current GP Element Sets (NORAD TLE / SupGP) vs Census Economic Time Series Database (MRTS, M3, Housing, Construction)
Which building products data provider data fits your job: CelesTrak Current GP Element Sets, or Census Economic Time Series Database. API, files, or your warehouse. Daily, weekly, or hourly.
CelesTrak Current GP Element Sets (NORAD TLE / SupGP)
Census Economic Time Series Database (MRTS, M3, Housing, Construction)
Where the fields line up
No shared field names. These two answer different questions.
| Field | CelesTrak Current GP Element Sets | Census Economic Time Series Database |
|---|---|---|
OBJECT_NAME | Common name of the space object. | not in this set |
OBJECT_ID | International designator (COSPAR ID) in YYYY-NNNAAA form. | not in this set |
EPOCH | UTC epoch of the element set. | not in this set |
MEAN_MOTION | Mean motion in revolutions per day. | not in this set |
ECCENTRICITY | Orbital eccentricity (dimensionless). | not in this set |
INCLINATION | Orbital inclination in degrees relative to the equator. | not in this set |
RA_OF_ASC_NODE | Right ascension of the ascending node in degrees. | not in this set |
ARG_OF_PERICENTER | Argument of perigee in degrees. | not in this set |
MEAN_ANOMALY | Mean anomaly in degrees at epoch. | not in this set |
EPHEMERIS_TYPE | Ephemeris type flag from the source element set (usually 0). | not in this set |
CLASSIFICATION_TYPE | Classification code for the element set (e.g., U = unclassified). | not in this set |
NORAD_CAT_ID | NORAD catalog number of the object. | not in this set |
Coverage, side by side
| CelesTrak Current GP Element Sets | Census Economic Time Series Database | |
|---|---|---|
| Geographic | None carried - orbit regime stands in for place | `geo_idx` / `geo_level_code` - US totals throughout |
What each contains
Pick by fit, not by loyalty.
| CelesTrak Current GP Element Sets | Census Economic Time Series Database | |
|---|---|---|
| Row identity | `NORAD_CAT_ID` plus `OBJECT_ID` (COSPAR designation) | `cat_idx` / `category_code` (NAICS-based, e.g. 4441) |
| Time anchor | `EPOCH` - UTC instant with sub-second precision | `per_idx` / `per_name` - month-year period label (Jul-2026) |
| Observed value | Six orbital elements per row (`MEAN_MOTION`, `ECCENTRICITY`, `INCLINATION`, `RA_OF_ASC_NODE`, `ARG_OF_PERICENTER`, `MEAN_ANOMALY`) | One typed scalar `val` / `cell_value` under declared units (MLN$, K units, RATIO) |
| Measure typing | Implicit - each element is its own named column | Explicit `dt_idx` / `data_type_code` (SM sales, VS shipments, TOTAL units) |
| Qualifier flag | `CLASSIFICATION_TYPE` (U = unclassified) | `is_adj` / `seasonally_adj` (adjusted versus not) |
| Revision trail | `ELEMENT_SET_NO` counter plus `REV_AT_EPOCH` revolution count | `error_data` flag marking cells that carry a sampling-error annotation |
| Geography | None carried - orbit regime stands in for place | `geo_idx` / `geo_level_code` - US totals throughout |
What each does better
CelesTrak Current GP Element Sets
Per-object geometry at catalog scale. Each row resolves one object's orbit completely enough to propagate: mean motion of 15.49544542 revolutions per day for the ISS sample row (epoch 2026-08-21T03:30:31 UTC), eccentricity 0.00076753, inclination 51.6331 degrees, then right ascension, argument of perigee, mean anomaly, the BSTAR drag term and mean-motion derivatives. Multiply a dozen-plus descriptors by 35,000 objects and you hold the substrate for pass prediction, conjunction screening and antenna pointing; see two-line element sets.
Curated constellation groups. Roughly 60 named groupings sort the catalog - space stations, GNSS, weather, cubesats, and a communications estate spanning active geosynchronous slots (with a movers-only view), the GEO protected zone, Intelsat, SES, Eutelsat, Telesat, Starlink, OneWeb, Qianfan, Kuiper, Iridium NEXT, Orbcomm and Globalstar. A separate Supplemental GP section adds higher-accuracy elements for selected operators.
A live data-model edge case. The five-digit catalog-number space filled up on 2026-07-11 - object number 100000, named Saramago - so new arrivals carry six-digit identifiers that the legacy two-line encoding cannot represent. Few catalogs let analysts watch their own format transition in the rows.
Census Economic Time Series Database
The whole demand chain in one estate. Dealer sales through MRTS, down to NAICS 444 building material and supplies dealers and 44413 hardware stores; factory output through M3 manufacturers' shipments, inventories and orders, with wood products, nonmetallic mineral products and construction materials and supplies broken out as categories; construction put in place, split residential, nonresidential and detailed nonresidential building types; new residential construction with permits, starts, under-construction and completions, divided single-family versus 5+ unit; and housing vacancies and homeownership. Twenty-one programs ride together; see MRTS monthly retail trade series.
Depth measured in decades. New residential construction reaches January 1959 in thousands of units; MRTS dealer panels and M3 factory series start January 1992 - the captured MRTS package runs to Jul-2026 with sales, inventories and inventory/sales ratios; construction put in place begins 1993 in millions of dollars. Around 200,000 rows sit in the MRTS panel alone, and housing starts alone give a complete post-war build-cycle record.
Statistical craft the orbital catalog does not attempt. Seasonally adjusted and unadjusted variants sit side by side, sampling-error annotations flag individual cells (error_data), and revisions are handled openly - current-month estimates print preliminary and firm up as reports arrive. For forecasting work, value of shipments with that treatment beats raw precision.
The verdict
Verdict: sample both, pick by fit - the question decides. If your question names an asset - where is this transponder platform, when does it rise over a receive site, is this constellation holding its shell - CelesTrak Current GP Element Sets (NORAD TLE / SupGP) is the instrument shaped for it. If your question names a market - are dealers restocking, are factories shipping more wood products, did housing starts and construction spending move together this quarter - Census Economic Time Series Database (MRTS, M3, Housing, Construction) answers it with seven decades behind it.
Quality does not break the tie: 10/10 against 9/10 is a rounding difference, not a ranking. Cut each sample to the objects, months and measures you actually work with, and let the returned rows make the call rather than the brand names.
Sample both, pick by fit. See CelesTrak Current GP Element Sets · See Census Economic Time Series Database
Fair questions
Is CelesTrak Current GP Element Sets better than Census Economic Time Series Database (MRTS, M3, Housing, Construction)?
Different instruments for different questions. The element-set catalog resolves where roughly 35,000 orbiting objects are and how their orbits decay, seventeen parameters per row. The Census database measures American demand - dealer sales, factory shipments, construction spending, housing starts - in monthly series back to 1959. Sample both, pick by fit: assets versus markets.
Which dataset covers more history?
The Census database, decisively: new residential construction runs from January 1959, dealer sales and factory series from January 1992, construction spending from 1993. The element sets carry current epochs - each row describes an orbit as fitted now, with an element-set revision counter showing how many times that object's fit has been superseded, not a decades-deep archive.
Do the two datasets overlap anywhere?
On structure, not substance. Both identify rows (NORAD catalog number versus NAICS-based category code), stamp both with a time anchor (sub-second UTC epoch versus a month-year label such as Jul-2026) and qualify both with flags (classification code versus seasonal adjustment). Beyond that, one dictionary spends its fields on orbital geometry, the other on measures, geography and units.
Which one should a building-products analyst sample first?
Start with [Census Economic Time Series Database](/datasets/building-products/census-economic-time-series-database-mrts-m3-housing-constru): MRTS dealer sales for NAICS 444, M3 shipments for wood products and construction materials, housing starts and construction put in place map directly onto demand. Add the element sets only if satellite distribution touches your analysis - the communications constellations it tracks carry the signals the ground economy consumes.
Can Datadory deliver both datasets together?
Yes. Either record arrives alone or merged onto one delivery calendar - aligned on period and identity so the join is done before it reaches you, delivered daily, weekly, or hourly, your call. Name the objects, categories and date windows when you request the sample and it lands pre-cut, with field definitions and coverage profiles attached.