Digital Realty Trust
Real Estate
Operator Signal: TAILWIND
Revenue growth is accelerating. This company is seeing consistent demand expansion, good signal for adjacent markets.
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Quarterly Earnings History
What This Means for Operators
Digital Realty Trust is in growth mode. Revenue is trending up quarter-over-quarter, which means the markets they serve are expanding. If you sell into the same ecosystem or serve similar customers, this is a green light.
When DLR grows, they hire, they increase vendor budgets, and their customers have more budget too. Follow the money.
Data from SEC EDGAR. View original filings: Digital Realty Trust SEC Filings
Frequently Asked Questions
Digital Realty Trust (DLR) currently has a TAILWIND operator signal with HIGH confidence. This signal is based on quarterly revenue trends and earnings patterns across 8 quarters of data.
Digital Realty Trust's latest reported revenue is $1.6B, representing +14.3% year-over-year growth. Latest EPS was $0.46.
Based on 8 quarters of earnings data, Digital Realty Trust shows a TAILWIND signal. Revenue is trending upward, indicating growth.
Digital Realty Trust's quarterly (10-Q) and annual (10-K) filings are available on SEC EDGAR. We analyze these filings to extract revenue, EPS, and net income data for our operator signal calculations.
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Operator signals are derived from quarterly revenue trends, EPS patterns, and net income direction across multiple quarters. Signals indicate momentum direction, not stock recommendations.
The this entity record above pulls directly from SEC EDGAR 8-K filings. What follows is the per-entity context — how this entity sits in the broader U.S. public-company earnings disclosures distribution and which underlying factors drive the headline numbers.
Every number on this page links back to SEC EDGAR 8-K filings; the methodology page describes the inputs, refresh cadence, and known limitations of the underlying data product.
Practical use of this page is in combination with the comparison and ranking pages elsewhere on the site, which surface the same data for this entity’s peers within U.S. public companies. A single-entity reading without peer context can be misleading when an entity is an outlier on one axis but typical on another.
Source: SEC EDGAR 10-K filings, 2026.