Top 10 Best Self Storage Data Services of 2026

CBRE is a strong fit for buyers who need market-level views that can connect to operator decisions like expansion timing and performance tracking. Facility intelligence outputs are oriented toward commercial real estate use cases, including identifying properties and building comparable sets for market monitoring. Delivery is typically geared toward controlled ingestion by analytics teams, which reduces ambiguity about dataset definitions.

A practical tradeoff is that the integration path often relies on CBRE-enabled provisioning rather than purely self-serve automation. CBRE works best when an internal data team can define ingestion formats, map fields into existing schemas, and run scheduled refreshes for dashboards.

Berkadia’s self-storage data coverage is oriented toward facility census and property screening needs used in underwriting and ongoing portfolio monitoring. Its research output is aligned to common storage decision workflows such as competitive set framing, trade-area style analysis, and performance benchmarking across a market footprint. Teams get stronger traction when the data is consumed inside established investment or asset management processes that already standardize assumptions and reporting templates.

A key tradeoff is that Berkadia is not positioned as a fully self-serve data API for raw unit-level feeds, so automation depends on the agreed delivery pattern. The service fits best when a team needs consistent dataset refreshes for internal review meetings and for downstream valuation models.

Cushman & Wakefield is a fit for teams that want storage-specific market intelligence anchored to broader commercial real estate research processes, not just unit-level data scraping. Facility-level reporting is commonly used for trade-area interpretation, competitive comp set context, and move and occupancy trend analysis for planning cycles. Governance is typically delivered through vetted research outputs and repeatable methodology, which reduces variation between analyst runs when the same market scope is reused.

A tradeoff is that data access patterns often depend on engagement-based delivery rather than standardized API provisioning for high-throughput pipelines. Teams planning quarterly planning updates work best when they can align to recurring market packs and benchmarking cycles, and they can ingest files into their own data warehouse.

Radius+ is a self storage data service provider focused on operational and competitive inputs for storage operators and analytics teams. Core capabilities center on facility and inventory coverage used for portfolio and market analysis, with outputs that support unit-level performance comparisons.

Radius+ also supports workflows that feed rental and occupancy style reporting pipelines rather than only static reference files. The differentiator is how the service packages facility coverage and performance-style signals for repeated use in benchmarking and planning cycles.

Self Storage Association aggregates industry-facing self storage market information through its education, research publications, and policy work tied to the self-storage operator community. It is distinct in how it publishes occupancy and rental related benchmarking content as member-oriented industry resources rather than a contract-grade unit level data API.

Core capabilities center on industry reports, research outputs, and operational context that support planning, market discussions, and internal benchmarking conversations. For data buyers, its value is usually indirect through cited research and guidance rather than direct unit inventory extracts.

Northmarq delivers self storage market data used for facility census and unit inventory planning, with an emphasis on investor and operator workflows. The service is structured around facility-level coverage and performance indicators, which supports supply and demand comparisons across specific trade areas.

Northmarq also supports operational planning needs like assessing occupancy conditions and rental rate benchmarks tied to geography and market segmentation. Automation depends on the available export and integration methods, so teams typically use it through analyst workflows or data feeds rather than ad hoc charting.

SkyView Advisors differentiates through a data services focus aimed at self-storage operators and analysts that need facility-level market inputs and reporting outputs. The service centers on pulling and structuring market and facility intelligence for workflows like benchmarking and performance comparisons across geographic or competitive sets.

It also supports ongoing operational data use cases such as rental-rate and occupancy-style reporting workflows rather than one-off market snapshots. Integration depth is oriented around feeding those datasets into internal analytics and reporting pipelines with repeatable extracts or exports.

JLL delivers self-storage market data with an established property-data footprint and built-for-commercial-real-estate workflows. Its core capability is market and facility intelligence tied to underwriting and portfolio analysis use cases, with data products intended for recurring reporting and decision cycles.

Buyers typically use JLL outputs for facility census, unit inventory views, and occupancy and rate analytics that support market sizing and performance checks. JLL also supports integration into internal reporting workflows, but the service focus is more consulting-to-data consumption than self-serve unit-level API exploration.

Marcus & Millichap delivers self-storage market data through its real estate intelligence and analytics services tied to investment research and brokerage workflows. It is distinctive for combining facility and market intelligence with an operator-oriented perspective used for underwriting, comp set building, and decision support.

The strongest fit is recurring analysis where market trends and property comparisons must translate into actionable investment narratives across multiple regions. Data delivery is geared toward structured research use rather than high-throughput unit-level extracts for automated scoring pipelines.

Newmark provides self-storage market data through a set of storage-focused datasets tied to its real estate research and advisory operations. The coverage is oriented to facility census and unit inventory style inputs that feed property-level benchmarking, competitive comp sets, and rent and occupancy analysis.

Integration and automation work tend to center on pulling curated data extracts and aligning them to facility identifiers rather than exposing a broad, programmable analytics API. Newmark also supports workflows that map market conditions to operational metrics such as tenant turnover and move activity.