Diversified REITs data: tenant economics and the listed tape, in one catalog. · Head-to-head
BLS Public Data API - NAICS 56 Employment Series (CEU6056000001) vs Tiingo Financial Market Data API
Which diversified reits data: tenant economics and the listed tape, in one catalog. data fits your job: BLS Public Data API - NAICS 56 Employment Series, or Tiingo Financial Market Data API. API, files, or your warehouse. Daily, weekly, or hourly.
BLS Public Data API - NAICS 56 Employment Series (CEU6056000001)
Tiingo Financial Market Data API
Where the fields line up
No shared field names. These two answer different questions.
| Field | BLS Public Data API - NAICS 56 Employment Series | Tiingo Financial Market Data API |
|---|---|---|
seriesID | BLS series identifier. | not in this set |
year | Observation year. | not in this set |
period | Observation period code, M01 through M12 for the twelve months of the year. | not in this set |
value | All employees in thousands of persons, not seasonally adjusted. | not in this set |
footnotes | Footnote codes riding beside the observation, such as P for preliminary. | not in this set |
Results.series | Container object holding the returned series, each with its identifier and its block of observations. | not in this set |
status | Status marker stating whether a delivery succeeded. | not in this set |
responseTime | Processing time in milliseconds, recorded for each delivery. | not in this set |
message | Informational text accompanying a returned series. | not in this set |
date | not in this set | documented |
open | not in this set | documented |
high | not in this set | documented |
Coverage, side by side
| BLS Public Data API - NAICS 56 Employment Series | Tiingo Financial Market Data API | |
|---|---|---|
| Geographic | United States (national) | United States - US-listed equities and ETFs, every listed REIT included |
| Temporal | Monthly observations back to 1939, roughly 1,000 rows | Variable by ticker; first and last dates of available history declared per ticker |
| Granularity | One observation per month for one industry-level series | One row per ticker per session, plus corporate actions, fundamentals and news events |
What each contains
They tie on 1 attribute. Pick by fit, not by loyalty.
| BLS Public Data API - NAICS 56 Employment Series | Tiingo Financial Market Data API | |
|---|---|---|
| Publisher | U.S. Bureau of Labor Statistics | Tiingo |
| Subject lens | Federal labor statistics: Current Employment Statistics national series CEU6056000001 - all employees, thousands, administrative and support and waste management and remediation services (NAICS 56), not seasonally adjusted | Commercial market data: eleven documented families spanning end-of-day prices, fundamentals, dividends, splits, news, crypto, forex and realtime equity prints |
| Unit of analysis | One observation per month for one industry-level series | One row per ticker per session, plus corporate actions, fundamentals and news events |
| Geographic coverage | United States (national) | United States - US-listed equities and ETFs, every listed REIT included |
| Temporal reach | Monthly observations back to 1939, roughly 1,000 rows | Variable by ticker; first and last dates of available history declared per ticker |
| Finest granularity | One monthly print per industry, not seasonally adjusted | Daily end-of-day bars, resampleable to weekly or monthly, with realtime families beside the archive |
| Documented fields | 9, definitions verified | 19, definitions verified |
| Formats delivered | JSON, plus text tables with annual averages | JSON or CSV |
| Rubric rating | 8 out of 10 (catalog average 7.81 across 1,744 datasets) | 8 out of 10 (catalog average 7.81 across 1,744 datasets) |
| Best for | Sector-scale workforce and demand-side measurement | Security-level pricing, distributions and company context |
What each does better
the BLS NAICS 56 Employment Series
One number, zero ambiguity. The entire record is the sector's payroll. The two most recent observations run July 2026 at 9,124.4 thousand (flagged preliminary) against June 2026 at 9,161.1 thousand - a 36.7-thousand step down between consecutive prints. Any question shaped like 'how large is demand-side support services right now' resolves without a single join.
Depth no equity archive matches. Monthly observations reach to 1939, roughly 1,000 rows for one continuous industry series, with year-range windows selectable on request. See the current employment statistics program behind it.
Shock measurement is already in the record. January 2020 stood at 8,974.3 thousand; the April 2020 trough hit 7,555.9 thousand - a 1,418.4-thousand collapse, 15.8 percent. The rebound to 9,124.4 thousand by July 2026 recovers 20.8 percent from that trough and leaves the sector 1.7 percent above its pre-pandemic level.
Revision status travels in-row. The footnotes column carries P for preliminary prints, so preliminary-versus-final is a field, not a footnote hunt. More at the U.S. Bureau of Labor Statistics source profile.
the Tiingo Financial Market Data API
Corporate actions arrive as columns, not footnotes. divCash carries the dividend paid on a date that doubles as the ex-date, and splitFactor absorbs splits and distributions - exactly the machinery corporate actions work needs, and REITs are distribution machines.
Share-class hygiene. Dashes replace dots (BRK-A, SPG-P-J), the same convention REIT preferred series follow - a small detail that prevents a whole class of screener mis-joins. Background at the Tiingo source profile.
Where they're equivalent
More than the labor-versus-capital split implies.
- Same slice, same score. Both sit among the 8 primary diversified REITs records and both rate 8 out of 10 against the 7.81 catalog-wide average, with fully verified field definitions on each side.
- JSON first. Both deliver JSON as the primary container; Tiingo adds CSV and BLS adds text tables carrying annual averages.
- US-centered. One is a national statistical series, the other a US-listed tape - neither reaches outside American geography.
- Neither touches buildings. No property-level rents, occupancy or net operating income exists on either side. Both records observe the industry from outside: the labor market it employs on one side, the capital market that funds it on the other.
- Single publisher each. One federal statistical agency, one commercial vendor - no aggregation layer sits between either record and its origin.
Fair questions
Which archive reaches further back?
The BLS series, decisively: monthly observations running to 1939, roughly 1,000 rows for one continuous industry series.
Do the two field dictionaries overlap?
Only on the spine: an identifier, a period stamp, one measured quantity and some form of annotation. Nine fields versus nineteen.
Can Datadory deliver both records together?
Yes - as a denominator-plus-numerator overlay. Datadory ships either record alone or merged onto one calendar with the period alignment finished before delivery - daily, weekly, or hourly, your call.