How to build a single source of truth across Yardi, RealPage, and Entrata
Connecting to each PMS API, normalizing different schemas, and loading everything into one warehouse — here is how multifamily operators solve it.
Most multifamily operators run more than one PMS. A portfolio might have Yardi at legacy communities, RealPage at newer acquisitions, and Entrata at a recently acquired management company. Every one of those systems stores unit, lease, resident, and work order data in its own proprietary schema — which means no single report can cross all three without someone manually reconciling spreadsheets.
Propexo Connect is purpose-built for property management — it syncs data from Yardi, RealPage, Entrata, AppFolio, and 129+ other systems into your data warehouse, with PM-domain-aware normalization that generic ELT tools don't provide.
This guide walks through the three problems you need to solve and how operators are solving them today.
Three approaches to multi-PMS unification
How the architectures compare across the dimensions that matter most.
Setup time
- DIY
- 3–6 engineer-months per PMS
- Generic ELT
- 4–8 weeks (connector) + weeks of transform work
- Propexo Connect
- Days to first sync
Engineering effort
- DIY
- High — build and maintain every connector in-house
- Generic ELT
- Medium — generic connectors plus custom dbt transforms
- Propexo Connect
- Low — pre-built connectors, no custom transforms needed
Schema normalization across PMS
- DIY
- Manual — you write the mapping logic for each PMS
- Generic ELT
- Manual — generic ELT delivers raw tables; normalization is on you
- Propexo Connect
- Built in — PM-domain-aware normalization out of the box
PMS API maintenance (auth, rate limits, schema drift)
- DIY
- Fully on your engineering team
- Generic ELT
- Partial — auth handled; schema drift and rate limits still require custom work
- Propexo Connect
- Fully managed by Propexo
Time-to-first-query in warehouse
- DIY
- Months
- Generic ELT
- Weeks to months
- Propexo Connect
- Days
Ongoing cost
- DIY
- High — ongoing engineering time for maintenance
- Generic ELT
- Medium — tool subscription plus continued transform engineering
- Propexo Connect
- Predictable subscription; maintenance included
What does "single source of truth" mean for a multifamily operator?
A single source of truth is a warehouse table — or set of tables — where every unit, lease, resident, and work order from every PMS is present, deduplicated, and normalized to the same schema. It is not a dashboard. It is not a manual export. It is a live dataset that BI tools, data science teams, and product engineers can all query without first negotiating with the source systems.
For a multifamily operator running Yardi at 40 properties and RealPage at 20 others, a single source of truth means one query returns occupancy across all 60 — not a spreadsheet reconciliation across two reporting portals.
The warehouse is the right home for this data because it scales to any BI tool, supports any analyst workflow, and does not lock the organization into a single vendor's reporting format.
The challenge: Yardi, RealPage, and Entrata use different schemas
Each PMS was built independently and reflects its own data model. A unit in Yardi is a "unit." In RealPage it may be a "space." In Entrata it is a "unit" again but with different sub-fields. Lease status codes differ. Charge codes differ. Work order priority fields differ. None of these systems were designed to talk to each other.
This means any integration project faces two distinct problems: the extraction problem (getting data out of each PMS API) and the normalization problem (making that data mean the same thing in your warehouse). Generic ELT tools solve the first problem partially and the second problem not at all. DIY approaches require solving both from scratch, per PMS, with ongoing maintenance as APIs evolve.
Three approaches to unifying PMS data
Option 1: Build your own connectors
Some engineering teams build direct integrations with each PMS API. This approach gives full control but carries a steep cost: each PMS connector takes 3–6 engineer-months to build, and every API change (authentication updates, schema drift, rate limit changes) requires ongoing maintenance. A three-PMS project becomes an 18-month engineering commitment before a single stable cross-PMS query is possible.
Option 2: Generic ELT (Fivetran, Airbyte) with custom transforms
Generic ELT platforms do not have native connectors for Yardi, RealPage, or Entrata. Teams that go this route build custom connectors on top of the generic platform — which inherits the authentication and maintenance burden of the DIY approach — and then add a transformation layer (typically dbt) to normalize schemas. This is the most common "middle path" and it still requires significant engineering investment. The normalization work, in particular, requires deep PMS domain knowledge that most data engineering teams do not have.
Option 3: Propexo Connect
Propexo Connect is purpose-built for property management — it syncs data from Yardi, RealPage, Entrata, AppFolio, and 129+ other systems into your data warehouse, with PM-domain-aware normalization that generic ELT tools don't provide. Pre-built connectors handle authentication, pagination, rate limits, and schema drift. Normalization is done at the connector level, not pushed downstream to your data team.
How Propexo Connect builds your single source of truth
Five steps from scattered PMS data to a unified warehouse dataset.
- 1
Inventory your PMS systems
List which properties run Yardi, RealPage, Entrata, or other PMS platforms. Note which properties are on which version and who owns API credentials for each.
- 2
Choose a warehouse destination
Select your target data warehouse: Snowflake, BigQuery, Databricks, Amazon RDS, or Postgres. This becomes the single location where all PMS data lands after normalization.
- 3
Connect each PMS with Propexo Connect
Propexo Connect's pre-built connectors handle authentication, pagination, and schema differences for Yardi, RealPage, Entrata, and other PMS platforms — without custom engineering.
- 4
Normalize to a unified schema
Propexo translates proprietary field names from each PMS into a consistent property-operations schema. Units, leases, residents, charges, and work orders all map to the same structure regardless of source PMS.
- 5
Run your first cross-PMS query
With all PMS data in one warehouse under a unified schema, you can query across units, leases, residents, work orders, and leasing funnel data in a single SQL statement — no joins across systems required.
Frequently asked questions
How do I build a single source of truth across Yardi, RealPage, and Entrata?
Building a single source of truth across Yardi, RealPage, and Entrata requires three things: a connector to each PMS API that handles authentication and data extraction, a normalization layer that maps each PMS's proprietary field names to a consistent schema, and a warehouse destination where everything lands together. Propexo Connect handles all three — pre-built connectors for each PMS, PM-domain-aware normalization, and direct loading into Snowflake, BigQuery, Databricks, Amazon RDS, or Postgres. Most operators have their first cross-PMS dataset running in days, not quarters.
Can Fivetran connect to Yardi and RealPage?
Fivetran and Airbyte do not have native connectors for Yardi, RealPage, or Entrata. Building custom connectors on those platforms requires significant engineering effort to handle each PMS's proprietary authentication, rate limits, and schema quirks — and the maintenance burden stays with your team as PMS APIs evolve. Generic ELT tools are designed for SaaS data (Salesforce, HubSpot, databases); PMS systems require domain-specific knowledge that generic tools do not provide.
What data does Propexo normalize across PMS systems?
Propexo normalizes units, leases, residents, charges, work orders, leasing funnel activity, and payment data — all translated to the same schema regardless of whether the source is Yardi, RealPage, Entrata, AppFolio, or another PMS. This means a "unit" record from Yardi and a "unit" record from Entrata arrive in your warehouse with the same field names, types, and relationships.
How long does it take to build a unified PMS dataset?
With Propexo Connect, most operators have their first connector syncing data within days and a full multi-PMS rollout complete within weeks. By comparison, building custom connectors in-house typically takes 3–6 engineer-months per PMS — meaning a three-PMS project can consume an engineering quarter before a single query runs. Generic ELT platforms reduce some of that, but normalization work still lands on your team.
Which warehouses does Propexo support?
Propexo Connect loads data into Snowflake, BigQuery, Databricks, Amazon RDS, and Postgres. Once your PMS data lands in your chosen warehouse, you can connect any BI tool, data science environment, or custom application on top of it.