A RESO Case Study
Sticking to Nonnegotiable Requirements for Interoperability Allows Hive MLS to Achieve Growth Without Conversions
Background
This case study explores the obstacles to growth encountered by Hive MLS, previously known as the North Carolina Regional MLS, and the RESO standards-driven solutions implemented to address them.
One of the fastest-growing MLSs in the U.S., Hive MLS has more than 19,000 subscribers across four states as of March 2025, uniting 18 stakeholder MLSs and associations within its cooperative framework.
Hive MLS empowers its MLS partners by providing wholesale services via Hive Solutions, pooling resources to enhance their collective buying power. This enables local MLSs to access a range of services, including training, software and support in a manner that reduces costs and improves the quality of services available to real estate professionals and their clients.
Growing Pains
In 2021, the Hive MLS leadership team identified a pressing challenge concerning their data management flow amidst their rapid growth. New members wanted to join Hive MLS, but with each new MLS partner came a new MLS system with its own data idiosyncrasies that needed to be unified with the main Hive MLS database. The MLS decided it could not continue to rely on cosmetic data sharing methods that didn’t unify and centralize its databases, as a superficial standardization would fail to address underlying data disparities.
When evaluating methods to centralize its data operation, the MLS found various vendor offerings for “Front-End-of-Choice” (FEoC) models. Within these FEoC models, vendors centralize listing creation into a single, designated platform, while limiting alternative front ends to viewing and editing capabilities.
For Hive MLS, proceeding with data unification in this manner would mean subscribers accustomed to using one MLS software platform to add new listings would be compelled to adopt a different system for data entry, disrupting established workflows and not achieving the MLS’s goal of full platform flexibility.
Hive MLS wanted to avoid new MLS partners having to go through a “cutover” or “conversion” of MLS systems. Finding no current option to meet that need, the MLS considered a custom solution using open, well-tested standards to allow data to flow accurately between systems.
The Real Estate Standards Organization (RESO) had been releasing new standards and certifications that allow different systems to interact in data management and align with one another quickly and accurately. Hive MLS saw these standards as the solution to build its system.
The Vision: Growth Without Conversions
Hive MLS’s leadership envisioned a data management framework that prioritized complete interoperability between MLS systems. Subscribers would leverage their preferred platforms, whether FlexMLS, Matrix MLS, or custom-developed solutions by brokerages or new vendors, without the disruptions associated with system conversions or mandated tools. Data entered through any interface would integrate seamlessly into a centralized repository through a standardized Add/Edit functionality. The data would be available for sharing within the cooperative or beyond, at the discretion of individual participants.
MLSs commonly outsource the stewardship of their data to the organizations that manage their front-end member software. Hive MLS’s plan required enhanced control over its entire data operation, and its leadership team knew that in order to accomplish this vision, it was going to need to create a skilled technology team.
Assembling a Team
Few MLSs possess the internal technical resources to execute such an ambitious data initiative, a challenge acknowledged across the industry. Rather than assembling a large in-house team, Hive MLS addressed this need through strategic partnerships.
After a thorough vendor evaluation process, Hive MLS chose to partner with SourceRE to provide its core data infrastructure and to leverage CTO and software development services from SourceRE’s parent company, Modern.tech. This collaboration provided Hive MLS with access to a technical workforce with expertise in MLS data architecture and RESO standardization.
Hive MLS’s Nonnegotiables
Realizing the risks associated with undertaking an effort of this magnitude, Hive MLS had firm demands on the system requirements. It would need to empower the MLS with full management of its data operations while providing staff with tools flexible enough to handle diverse demands of subscribers, vendors and other stakeholders. These requirements included:
- Full Interoperability: The system needed to support full “Add/Edit” creation of listings from each MLS front end, not just “Edit.”
- Granular Data Control: MLS staff needed to be able to make updates to its data dictionary and control the schedule of data field and API updates without having to ask their vendors for permission. Participants and stakeholders also required the ability to exert detailed control over their data distribution.
- RESO-Based Architecture: The system needed to be architected from the beginning in compliance with RESO standards and in a manner scalable enough to support future certifications.
- Independent Database: The new, centralized database needed to be independent from any one MLS front-end system, decreasing reliance on third-party vendors.
- Unified Business Rule Validation: Business rules needed to be unified between Hive MLS and any new MLS vendor joining the implementation, and the system needed to validate these business rules to facilitate interoperability.
- Support for Local Fields: The solution needed to be versatile enough to support local fields from the participating MLS systems to fully facilitate interoperability and participant-level distribution controls.
- Beyond Listing Data: A solution that could scale beyond listing and property data was essential, allowing MLSs, their business partners or participants to integrate an expanding array of data sources without the complications tied to disconnected systems.
- Seamless Integration of New Vendors: A streamlined, efficient process was needed to incorporate new data instances, ensuring smooth expansion.
- High Security: State-of-the-art security, encryption best-practices and elimination of the risk of data access loss were critical to maintaining operational integrity.
- Marketplace Creation: With the other features enhancing the value of the data set, the system needed to be capable of generating a revenue stream through direct dissemination of data feeds to create shareholder value.
The Hive MLS Solution
Hive MLS and its vendor spent 2024 developing the database and API system to meet the outlined requirements. By Q1 2025, the new system was ready to serve as the technical backbone of Hive MLS’s interoperability efforts, pioneering the industry concept of a “Data Exchange.”
MLS Data Exchange (MDX)
The MLS Data Exchange (MDX) provides a model for lower-friction MLS consolidation. Hive MLS’s MDX establishes one of the most important features of an MDX: the unification of business rules. Ocusell was hired to audit, collect and unify business rules across all systems. As a result of this unification, Hive MLS’s MDX can validate all API calls attempting to write data into the database.
The MDX model enhances Hive MLS’s brand, allowing it to differentiate the front-end vendor from the unique value that the MLS itself brings directly to subscribers. It also creates important redundancies among front-end vendors should any vendor system experience downtime.
When Hive MLS decides to make changes to data or rules, all vendors have equal opportunity to implement these changes by simply using the API in accordance with Hive MLS’s rules. This drives innovation for Hive MLS’s brokers and agents, as it welcomes new vendors into an environment of healthy competition and member choice, while enabling brokerages the freedom to create their own white-labeled Add/Edit solutions based on standards.
As a wholesale cooperative, the MDX model aligns with the Hive MLS business model. MDX participation consolidates the data operation of participants but does not dictate the levels and methods of organizational partnership and consolidation that partners wish to achieve together. This flexibility allows Hive MLS to wrap its wholesale value proposition around the MDX implementation of enhanced data operations, creating a compelling value proposition for new MLS partners and their subscribers.
Enabled by RESO Standards
While MLS data independence and interoperability are not new concepts, they have been largely out of reach until recent years due to the lack of adopted standards around “writing” real estate data (Add/Edit).
With RESO’s recent certifications and endorsements, including the RESO Data Dictionary 2.0, RESO Web API Add/Edit and Webhooks, standardized Add/Edit interoperability is now realized for the industry and offers opportunities for modern MLS organizations to structure their foundational systems going forward.
Closing: A Step-By-Step Guide
This is the starting line. Hive MLS and its vendors are working out how best the various systems will integrate together for external use, and Hive MLS is now beginning to integrate front-end partners into its MDX foundation. For other MLSs that may be seeking the same goals, Hive MLS outlined its roadmap to completion. Below is the structured methodology employed:
- Data Aggregation: MLSs first initiate the data collection process by gathering API feeds from existing database instances to aggregate all relevant data, including listings, rosters, open houses and media files into the centralized independent database.
- Data Standardization: Once aggregated, data is normalized to eliminate inconsistencies, applying RESO Data Dictionary 2.0 mappings to standardize fields across platforms. Local field mapping follows, with the technical team consulting the MLS to align these fields for commonality. This ensures compatibility across stakeholder MLSs while preserving conditional visibility as determined by platform vendors.
- Data Deduplication: Unique identifiers are integrated during normalization to prevent duplication. This step also unifies roster and listing data, creating a cohesive dataset. To enhance accessibility, in Hive MLS’s implementation, its vendor hosts heavy media files – documents and virtual tours – via secure URLs to streamline agent access through single sign-on (SSO).
- Business Rule Consolidation: Business rule collection and alignment were required. A business rule audit is conducted for each MLS system in order to capture and clarify all current business rules. Once all the disparate rules are clarified, they are consolidated into one final compilation.
- MLS Data Feed Business Model Decisions: Combining the data from multiple MLSs can increase its appeal to vendors managing feeds like IDX and VOW for numerous subscribers, reducing sourcing complexities. The MLS and its stakeholders can consider the best business model for pricing these products.
- Provide API Access to FEoC Vendors: Using the updated data dictionary and updated business rules, the MLS turns on the API and provides access and documentation to FEoC vendors.
- Provide API Access to All Other Vendors: With new access requirements in place, the data distribution system is made available to other vendors and brokers.
The result is a scalable, interoperable data exchange that meets the MLS’s immediate needs and allows it to join a select group of MLSs pioneering interoperability and enabling intelligent MLS consolidation.
