Rental data has become a core input for automated valuation models. Rent estimates feed cap rates, gross rent multipliers, and income-based valuation logic that lenders and investors now expect. However, rental data providers differ widely in how they source data, which asset classes they cover, and how they deliver it. For data science teams, those differences show up directly in backtest results. This list covers nine rental data providers AVM teams can evaluate, with key features, ideal use cases, and pricing for each.
Comparison Summary
| Provider | Data Type | Asset Class | Delivery | Best For |
|---|---|---|---|---|
| Dwellsy IQ | Unit-level rent data, rent comps, rent indices | SFR, multifamily | API, S3, MCP, sheets | Rent estimates, rent comps, market-level signals and model training |
| Cotality | Rent estimates, ZIP-level trends | Single-family | API, cloud, flat file | Rent estimates with confidence ranges |
| ATTOM Data | Rental AVM, property records | Single-family | API, bulk, cloud | Joining rent to property records |
| RentCast | Rent estimates, listings, records | Residential | API | Self-serve prototyping |
| CoStar | Property-level rent, occupancy | Multifamily, commercial | Subscription platform | Multifamily valuation |
| Yardi Matrix | Researched rent, occupancy, forecasts | Multifamily (50+ units), BTR | Subscription platform | Large multifamily assets |
| Zillow (ZORI) | Repeat-rent index | All rentals | CSV download | Free benchmarking |
| Parcl Labs | Rental price feed, yields | Residential | API | Market-level signals |
| Rentometer | Rent estimates, comps | Residential | API, web | Spot checks |
1. Dwellsy IQ
Dwellsy IQ is a rental data provider built on the Dwellsy marketplace. Its rent data comes directly from property management systems, not from scraping or surveys. The dataset covers 17M+ listings across single-family rental (SFR), build-to-rent, and multifamily, with 250+ standardized attributes per unit. For AVM providers, it supports rent estimates, rent comps, market-level signals, and model training from a single source.
Key Features
- Unit-level rent data sourced from 30+ property management system integrations and 25,000+ property managers
- 250+ standardized attributes per listing
- URU (Unique Rental Unit Identifier) that tracks each unit over time for longitudinal analysis and backtesting
- Trends IQ rent indices across 800+ MSAs and 16,000+ ZIP codes, with history back to January 2020
- Delivery via REST API, AWS S3, MCP server, and spreadsheets
Best For
VM providers that need SFR and multifamily rent data for rent estimates, rent comps, market-level signals, and model training, especially teams running backtests before scaling.
Pricing
Pricing is not publicly listed — contact for a quote.
2. Cotality
Cotality, formerly CoreLogic, offers both a rent estimation model and market-level rental analytics. Its Rent Amount Model estimates monthly rent for single-family properties nationwide, including areas with few comparable rentals. Additionally, its Rental Trends product converts active listings and assessor records into ZIP-level time-series metrics.
Key Features
- Rent Amount Model with estimated rent, low and high estimates, and a forecast standard deviation score
- Nationwide coverage of attached and detached single-family homes
- Rental Trends metrics including rent per square foot, cap rates, and vacancy rates at the ZIP level
- Delivery via API, flat file, Snowflake, Databricks, AWS, Azure, and Google Cloud
Best For
Teams that want an off-the-shelf rent estimate with confidence ranges to use as a model input or benchmark.
Pricing
Pricing is not publicly listed. It varies by volume, geography, and delivery method.
3. ATTOM Data
ATTOM Data is a property data provider with a large public-records foundation. Its Rental AVM estimates monthly rental values for U.S. residential properties. The estimates draw on market data, comparable rentals, local trends, and property characteristics.
Key Features
- Rental AVM coverage for over 80 million single-family residences
- Integration with ATTOM’s broader property, tax, deed, and valuation datasets
- Delivery via API, bulk files, and cloud platforms
Best For
AVM teams already using ATTOM property records that want rent estimates joined to the same property IDs.
Pricing
Pricing is not publicly listed — contact for a quote.
4. RentCast
RentCast offers a developer-oriented property data API. It combines public records with rental and sale listing feeds to produce rent estimates, comparables, and market statistics. The self-serve setup makes it straightforward to test before committing.
Key Features
- Rent and value estimates with nearby comparables and distance from the subject property
- Property records covering 150+ million properties
- Active rental and sale listings plus historical market trends by ZIP code and city
- Free tier of 50 API requests per month
Best For
Smaller AVM teams and startups that want fast, self-serve API access for prototyping.
Pricing
Free plan with 50 requests per month. Paid plans scale by request volume, with enterprise plans available on request.
A fuller view of the rental market for your AVM
Feed your models unit-level rent data sourced directly from property management systems.
5. CoStar
CoStar is a commercial real estate information platform with a large multifamily research operation. It combines primary research, public records, and data from its Apartments.com network. As a result, its multifamily data includes rent, occupancy, and concession detail at the property level.
Key Features
- Approximately 38 million multifamily units tracked and 16 million monthly rent observations
- Peer comparisons covering concessions, rent growth, and occupancy
- Market forecasts under multiple economic scenarios across nearly 400 markets
Best For
Valuation teams focused on multifamily and commercial assets that need property-level rent and occupancy history.
Pricing
Subscription-based. Pricing is not publicly listed — contact for a quote.
6. Yardi Matrix
Yardi Matrix provides researched multifamily data on properties with 50 or more units. It covers rent, occupancy, sales history, and unit mix across U.S. multifamily markets. Furthermore, it includes data on build-to-rent communities.
Key Features
- Coverage across 184 multifamily markets
- Detailed unit mix, ownership, and management information
- Short- and long-range rent and occupancy forecasts at market and submarket levels
- Build-to-rent SFR community data
Best For
Models focused on large multifamily properties where unit mix and occupancy drive value.
Pricing
Subscription pricing based on markets and number of users. Exact pricing is not publicly listed.
7. Zillow Research (ZORI)
Zillow publishes the Zillow Observed Rent Index (ZORI), a repeat-rent index built from listings on its platform. The data is free to download from Zillow Research. It works well as a market-level benchmark rather than a property-level input.
Key Features
- Monthly rent index at metro, city, and ZIP levels
- Repeat-rent methodology that controls for changes in the mix of listed units
- Free CSV downloads
Best For
Teams that need a free, widely cited benchmark for validating model outputs and market-level trends.
Pricing
Free to download.
8. Parcl Labs
Parcl Labs is a residential real estate analytics company that offers data through an API. It publishes a rental price feed alongside market metrics such as rental price indices and gross yield. The API is aimed at quantitative and developer users.
Key Features
- Rental price feed and rental price indices across U.S. markets
- Gross yield and other investment metrics
- Credit-based API with developer documentation
Best For
Quantitative teams that want market-level rent and yield signals through an API.
Pricing
Credit-based. Current tiers are listed in Parcl Labs’ documentation.
9. Rentometer
Rentometer is a rent comparison tool that also offers an API. It returns rent estimates and nearby comparables for a given address and unit type. Consequently, it is a lightweight option for spot checks rather than bulk model training.
Key Features
- Rent estimates and nearby rent comparables by address
- API access for quick lookups and detailed reports
- Simple self-serve setup
Best For
Teams that need quick rent validation for individual properties or small batches.
Pricing
Credit-based API pricing is published on Rentometer’s website.
FAQ
What rental data do AVM providers need?
AVM providers typically need property-level rent observations with matchable attributes like bedrooms, bathrooms, square footage, and property type. Time-series history is also important for training and backtesting. Market-level indices help validate outputs and track trends.
How do I choose a rental data provider for my AVM?
Start with the asset class and geography your model covers. Then compare sourcing methodology, update frequency, historical depth, and delivery format. Running a pilot backtest against your existing data is the most reliable way to measure accuracy lift.
What is the difference between rent estimates and rent data?
Rent data is observed rent tied to specific units, such as listing or lease records. Rent estimates are modeled outputs derived from that data. AVM builders usually prefer observed data for training, and use third-party estimates as benchmarks.
Are free rental data sources good enough for AVMs?
Free sources such as Zillow’s ZORI and Census data work well as benchmarks. However, they are aggregated by geography and do not provide property-level records. Most production AVMs combine free benchmarks with a licensed property-level feed, such as Dwellsy IQ.
How often should rental data be refreshed in an AVM?
Refresh cadence depends on how quickly target markets move and how the model is used. Property-level rent data often warrants monthly or more frequent updates. Index and benchmark data can follow its published release schedule.
