Nasdaq Data Link (Quandl) - REIT Datasets

Not a curated REIT file - a marketplace, pointed at the right shelves. Nasdaq Data Link is the former Quandl, rebuilt as an exchange product: hundreds of financial, economic and alternative data products addressed by short code, each with a documented field list, a named publisher and a cadence statement. Queried for REIT-related series, it returns a small fraction of that catalog - which is precisely the value. Instead of one thin office REITs feed, you get the whole stack an office name actually needs: EOD price history for the listed tickers, standardized fundamentals per ticker per period, Commitment of Traders positioning and US economic series, all speaking the same row grammar. Datadory cuts that stack to the office universe - the ~14-18 constituent screens, the 41 office-sector names inside an 839-REIT universe - and ships the rows before the pitch.

One honest note first: the public catalog gates automated capture behind a JavaScript app, so our August 2026 research pass verified the row contracts against the platform's own documentation rather than quoting a live print. Values below are rounded placeholders; the shapes are exactly what ships.

Two grains, both real:

# Grain 1 - catalog result row (one per product)
dataset_code : EOD              name      : End of Day US Stock Prices
publisher    : Nasdaq           frequency : daily
description  : Daily open/high/low/close/volume for US-listed equities

# Grain 1 - catalog result row (third-party vendor shelf)
dataset_code : SF1              name      : Core US Fundamentals
publisher    : Sharadar         frequency : quarterly

# Grain 2 - time-series row (one per security per session)
ticker       : BXP              date      : 2026-08-21
open 81.20     high 82.05     low 80.75     close 81.88
volume       : 2418300

The first grain answers "what exists" - every product arrives as a short code, a human-readable name, a publisher, a cadence and a coverage sentence. The second grain answers "what it looks like" - dated rows keyed on security, which is the shape most office REIT work actually consumes.

Six columns document every listing in the dictionary captured during the research pass; the five below form the spine, and Name types are exact:

The catalog carries one further boolean flag recording how each shelf is sold. Which shelf a given product occupies is settled when your sample is cut, so that detail travels with the sample rather than on this page - ask for the products by code and the answer arrives attached to the rows.

Three chips, honestly drawn:

• Geography - Global, weighted toward US-listed securities and US economic series. Office REITs trade overwhelmingly in New York, so the US weighting lines up with the sector rather than fighting it.
• Temporal - Varies by product; equity price histories extend back decades while economic series vary by program. A multi-decade bar history for a name like BXP or VNO is the norm, not the exception.
• Granularity - Per-security time series and tabular datasets side by side. One catalog serves both the dated-row jobs (price screens, event windows) and the entity-level ones (statement archives, positioning tables).

API, files, or your warehouse. Daily, weekly, or hourly.

Tables land however your stack wants them - pushed to storage, served on request, or synced into your database, as JSON or CSV for the heavy extracts. The cadence choice maps to the work: hourly suits a desk watching BXP through an ex-dividend date or an earnings print, daily is the backtest standard with one bar per session, weekly fits board reporting where the trend matters more than any single print, and quarterly matches the natural rhythm of statement archives and positioning tables. Name the products, the field cut and the cadence when you request the sample; the sample ships first either way. Get a sample of this dataset and both row shapes above arrive cut to your tickers.

A catalog this broad earns its keep in specific office REITs jobs:

• Fix the roster before modeling it. Ask how many office REITs exist and one screen says ~14-18 constituents, another counts 41 office-sector companies inside an 839-REIT universe. Pulling candidate lists out of a catalog with documented publisher metadata beats a vibes-based universe you rebuild every six months.
• Price the event window, not just the quarter. A sector yielding roughly 6% manufactures phantom losses at every ex-dividend date unless bars arrive adjusted alongside the as-traded close - the documented time-series shape carries both conventions.
• Join statements onto bars on ticker plus date. Fundamentals keyed per ticker per reporting period meet price rows keyed per security per session, so a standardized-statement-plus-price-history stack is a two-key join rather than spreadsheet surgery.
• Overlay positioning and macro. Commitment of Traders tables and US economic series ride in the same catalog, letting a desk test whether an office name lagged because management slipped or because every REIT slipped.
• Benchmark traded against fundamental views. Traded total return against appraisal-based return separates sentiment from fundamentals - the gap the Nareit Office REIT Sector Hub aggregate rows quantify, where the sector carried 86.9% occupancy and 2.1% NOI growth in the 2026-Q1 T-Tracker shape.

Five of Datadory's eight personas carry this record in the office REITs slice:

• Developers & data-product builders - short codes and documented dictionaries make integration legible; the catalog's uniform addressing means one client handles every product.
• Investors & quant researchers - decades-deep bar histories plus statement archives is the canonical screening stack for a sector trading on expectations.
• Data scientists - two clean grains, dated rows and entity-period rows, normalize into one schema without hand-parsing.
• Market researchers - publisher metadata and catalog descriptions map the landscape before anyone commits to a vendor.
• Competitive intel & product teams - see how the slice's monitoring sources rank on the competitive intel product teams use cases page.

Notes worth reading next:

• Office REITs hub - the pooled view of the industry slice, from T-Tracker aggregates to building stock.
• Financial Modeling Prep vs this catalog - single-vendor statement depth against marketplace breadth; the scored trade-off for BXP, VNO and KRC work.
• REITNotes 839-REIT database - the fixed 41-name office roster with FFO, the complement to a broad catalog screen.
• Yahoo Finance quote pages - quote-history bars with adjusted close for individual tickers.
• Seeking Alpha office REIT symbol pages - the sell-side commentary layer beside the priced layer.
• Nasdaq source profile - everything we catalog from the exchange operator in one place.