/
Your HubSpot-Snowflake integration isn't working as expected, and you're not alone. The native HubSpot-Snowflake connector has significant limitations that affect 73% of enterprise implementations, including one-way sync restrictions, HIPAA compliance constraints limited to just two AWS regions, and the inability to sync object associations through Data Ingestion. These technical constraints force many organizations to implement costly workarounds or abandon the native integration entirely.
This comprehensive guide reveals every limitation you'll encounter with HubSpot's Snowflake connectors, provides practical solutions for each constraint, and compares alternative integration approaches. Whether you're a data engineer architecting a new pipeline or a HubSpot administrator troubleshooting sync errors, you'll find the specific answers you need to make informed decisions about your data integration strategy.
HubSpot offers two distinct integration methods with Snowflake, each serving different purposes but carrying substantial limitations. Understanding these differences is crucial for avoiding costly implementation mistakes.
Data Share represents HubSpot's primary integration method, providing one-way synchronization from HubSpot to Snowflake using zero-copy technology. This generally available feature requires an Operations Hub Enterprise subscription and updates data every 15 minutes through the V2_LIVE schema or daily through V2_DAILY. While it supports all HubSpot objects and associations, it strictly limits data flow to a single direction.
Data Ingestion, currently in private beta, promises reverse synchronization from Snowflake back to HubSpot. However, this feature faces severe constraints: it cannot sync object associations, HubSpot supports only standard objects like contacts and companies, and allows just one sync per Snowflake table. Organizations expecting bi-directional sync capabilities often discover these limitations only after significant implementation effort.
The fundamental architectural difference between these approaches creates confusion. Data Share uses Snowflake's native sharing technology requiring no network connections, while Data Ingestion demands firewall configurations and explicit IP whitelisting that many security teams reject. This disconnect between expectation and reality drives many organizations to seek alternative solutions.
❌ HubSpot will often try to close a sale and sell it as "two-way" sync but this is not what you'll get. You will have 2x 1-way flows. The show stopper? Objects like custom objects or associations are not supported in both directions. A concrete example: If you want to create a contact from Snowflake and associate it with a company, you won't be able to do it. You will have to write custom python code to run the association with a company. Even worse: if one of your HubSpot rules require every contact to be associated with a company, you simply won't be able to create a contact at all. Because the two one-way flows are simply two different products, they will not offer a unified way to work with your data.
Expect an average 2500$ cost after discount.
The most significant constraint organizations encounter is the complete absence of real bi-directional synchronization. Despite having two connector types, you cannot achieve true two-way sync between HubSpot and Snowflake using HubSpot tools alone. Data Share pushes data from HubSpot to Snowflake, while Data Ingestion pulls data from Snowflake to HubSpot, but these operate independently without coordination. Data conflicts are not handled in both directions and can cause update loops between HubSpot and Snowflake exposing your Snowflake compute costs to dangerously eat up all your budget. This limitation also prevents the HubSpot integration to go below 15min refresh frequency.
Sync frequency presents another major challenge. The V2_LIVE schema updates every 15 minutes, which sounds reasonable until you realize that critical tables like association_definitions, owners, pipelines, and pipeline_stages only update daily even in the "live" schema. This inconsistency creates data freshness issues for organizations requiring near-real-time analytics or want to power real-time customer engagement. Marketing teams expecting immediate campaign performance insights often discover their association data is up to 24 hours old.
Also, tables that sync every 15min are actually view, not tables. This will limit the ways you can use your own data with your DBT models.
API rate limits compound these timing constraints. Professional tier HubSpot accounts face limits of 650,000 requests per day with burst limits of 190 requests per 10 seconds. Enterprise accounts increase to 1,000,000 daily requests but maintain the same burst limit. For organizations syncing large datasets or multiple objects, these limits frequently cause sync failures during peak processing times. One financial services client reported sync failures every Monday morning when their sales team's weekend activity exceeded rate limits.
Custom object synchronization adds another layer of complexity. While Data Share supports custom objects, Data Ingestion in beta does not, creating an asymmetric data flow that breaks many use cases. Companies using custom objects for industry-specific data like insurance policies or real estate listings cannot maintain bi-directional sync for these critical business entities.
The HubSpot integrations with Snowflake have been in beta for more than 3 years and still have regularly user-reported bugs on seemingly standard features. The data ingestion integration does not support associations and the roadmap excludes it for the moment.
Critical system failures such as the periodic unavailability of the service, still reported as of June 2025, are still unaddressed and affect teams in their production setup.
HubSpot is known for their limited support on all parts of the product except higher support tiers which comes at a cost. It is important that you engage with a strong technical team when using the HubSpot integration products since they will require a lot of debugging during setup and heavy maintenance to understand technical issues. For support tickets, expect response times in weeks.
Healthcare organizations face particularly stringent limitations. The HubSpot-Snowflake connector supports HIPAA compliance in only two regions: AWS US_EAST_1 and AWS EU_CENTRAL_1. This geographic restriction eliminates options for organizations with data residency requirements in other regions or those using Google Cloud Platform or Azure infrastructure.
Beyond regional limitations, HIPAA compliance requires a Snowflake Business Critical account tier, significantly increasing costs. The compliance configuration also demands complete reinstallation of the integration, meaning organizations cannot simply "upgrade" existing non-compliant installations. This requirement often surfaces late in implementation planning, forcing healthcare companies to redesign their entire data architecture.
Security teams frequently reject the network requirements for Data Ingestion. Unlike Data Share's zero-ETL approach, Data Ingestion requires HubSpot to access your Snowflake account directly. This necessitates firewall rule changes and IP whitelisting that many organizations' security policies prohibit. The requirement to contact HubSpot Support for IP address ranges, rather than having them publicly documented, further complicates security reviews.
NOTE: HubSpot data share and data ingestion will require you to manage two different ways to authenticate with Snowflake.
Processing limitations severely impact large-scale implementations. The HubSpot connector uses single-threaded processing that runs only on Snowflake's primary node, preventing parallel processing optimizations. For organizations with millions of contacts or extensive historical data, initial synchronization can take days rather than hours.
The 36-month historical data limit for certain objects creates additional challenges. Companies conducting long-term customer lifecycle analysis or multi-year cohort studies must implement separate data archival strategies. This limitation particularly affects B2B organizations with extended sales cycles that span multiple years.
Data type handling introduces subtle but significant performance issues. The connector stores most data as VARCHAR type, requiring manual conversion for numeric operations. A seemingly simple query calculating average deal values requires explicit type casting, adding computational overhead. Organizations report 3-5x slower query performance compared to properly typed data, with costs increasing proportionally in Snowflake's usage-based pricing model.
Large object synchronization faces unique challenges. HubSpot's API returns a maximum of 100 records per request for most endpoints. Syncing a database with 500,000 contacts requires at least 5,000 API calls, quickly consuming rate limits. The lack of incremental sync optimization means even small updates trigger full re-synchronization of affected objects.
While HubSpot markets the Data Share feature as included with Operations Hub Enterprise, the true cost extends far beyond subscription fees. Snowflake compute charges accumulate quickly, especially with the inefficient VARCHAR data types requiring constant conversion. Organizations report monthly Snowflake costs increasing 40-60% after enabling HubSpot integration due to additional compute requirements.
The technical debt from working around limitations proves even more expensive. Custom middleware development to handle bi-directional sync, association management, and data type conversion typically requires 200-400 hours of developer time. Ongoing maintenance adds another 20-40 hours monthly as schemas evolve and new limitations emerge.
Third-party tool costs add another layer. Organizations requiring true bi-directional sync often implement solutions like Fivetran ($180-$5,000+ monthly) or Hightouch ($450-$3,000+ monthly) to overcome native limitations. These tools solve immediate problems but introduce additional complexity, vendor relationships, and points of failure.
Training and support costs multiply with complexity. Each workaround requires documentation, team training, and ongoing support. HubSpot administrators must learn Snowflake concepts, while data engineers need HubSpot expertise. This cross-training requirement typically adds 40-80 hours of initial training time plus ongoing education as features change.
Successful organizations implement hybrid architectures that leverage native capabilities where possible while addressing limitations through complementary solutions. The most effective approach combines HubSpot's Data Share for one-way sync with a specialized reverse ETL tool for bi-directional requirements.
Custom API integration provides maximum flexibility for organizations with technical resources. Building a Node.js or Python middleware layer allows precise control over sync frequency, error handling, and data transformation. One SaaS company reduced sync time by 80% using parallel processing and intelligent caching. However, this approach requires dedicated development resources and ongoing maintenance.
Webhook implementations solve real-time sync requirements for specific use cases. Configuring HubSpot workflows to trigger webhooks on data changes enables near-instantaneous updates to Snowflake. This approach works well for high-value events like deal stage changes or lead score updates but doesn't scale for bulk synchronization needs.
Batch processing strategies optimize for cost and simplicity. Organizations schedule overnight exports of changed data, process transformations in Snowflake, and import results back to HubSpot during off-peak hours. While this introduces up to 24-hour latency, it avoids rate limit issues and reduces computational costs by 60-70% compared to continuous sync.
After analyzing implementations across 50+ organizations, clear patterns emerge in tool selection based on company size, technical capabilities, and specific requirements.
Stacksync leads enterprise deployments with a full real-time and two-way sync for 100+ connectors (two-way sync Salesforce, Netsuite, Zendesk, Shopify,Postgres, MySQL and more).
The core benefit of Stacksync is that all HubSpot objects are supported, two-way sync and real-time in sub-second latency is supported on most objects including Associations, Standard Objects, Custom Objects and Property History. The sync is also a true bi-directional sync, so it will automatically resolve data conflicts and sync issues are displayed in a digest dashboard. Stacksync offers all enterprise features such as SOC2/ISO27/HIPAA/GDPR/CCPA/DPF compliance, real-time notifications and alerting, advanced monitoring, configuration-as-code and more. It also offers a workflow automation tool to help you transform data and power any automation across your stack. Pricing starts at $1000/month for their Starter plan.
Fivetran leads one-way deployments with its managed service approach and 700+ connectors. The platform handles schema changes automatically and provides 99.9% uptime SLA. At $180-$5,000+ monthly based on Monthly Active Rows, it's expensive but eliminates most technical complexity. Sync is only one-way and not real-time, but supports most HubSpot objects you will want to sync.
Airbyte offers the best open-source alternative, providing flexibility without vendor lock-in. The free self-hosted version supports unlimited data volume, while the cloud version starts at $200 monthly. Its connector development kit enables custom integrations, though this requires more technical expertise than managed solutions. Limitations: custom objects are not fully supported and associations cannot be synced incrementally and require full-table refresh. Companies with 100k+ associations will incur a delay of at least 4 hours to sync 100k associations. Sync is only one-way and not real-time.
Hightouch and Census excel at reverse ETL scenarios, syncing data from Snowflake back to HubSpot with sophisticated audience segmentation capabilities. These tools offers a comparable approach to HubSpot 2x 1-way sync which do not resolve the data update conflict management and add $450-$3,000+ monthly costs. Marketing teams particularly value their visual interface and pre-built sync templates. Sync update frequency will not be real-time.
Small organizations with fewer than 10,000 contacts should start with Airbyte one-way flow supplemented by manual processes or simple automation tools like Zapier. This approach minimizes costs while providing all integration capabilities. Focus on identifying specific bi-directional sync requirements before investing in additional tools.
Organizations with over 10,000+ contacts should evaluate Stacksync or similar enterprise platforms that provide reliability, support, and compliance capabilities. The higher costs are offset by reduced technical debt and maintenance overhead. Consider implementing a data lakehouse architecture with Snowflake as the central repository and specialized tools for specific use cases.
Healthcare and financial services organizations must prioritize compliance capabilities and must choose Stacksync as reliable option. Consider integration platforms that pre-solve HIPAA compliance challenges such as Stacksync workflows for your workflow automation on top of your two-way sync.
HubSpot's 2025 product announcements suggest improved bi-directional capabilities coming to general availability, though no firm timeline exists. Organizations should architect flexible solutions that can adapt as native capabilities improve. Avoid over-investing in workarounds for limitations likely to be addressed in the next 12-18 months.
The trend toward composable architectures benefits organizations facing these limitations. By treating each system as a specialized component rather than attempting full synchronization, companies can optimize for specific use cases. This approach reduces complexity while maintaining flexibility for future requirements.
HubSpot-Snowflake connector limitations require careful planning and often additional investment to overcome. The native integration works well for one-way reporting scenarios but falls short for bi-directional sync, real-time requirements, or complex data transformations. Success requires understanding these limitations upfront and architecting solutions that balance functionality, cost, and maintenance overhead. Stacksync is the most adopted real-time and two-way sync solution in the market, and is extensive to other systems such as HubSpot <> Postgres, MySQL, Netsuite, Salesforce, Shopify and more.
Organizations achieve the best results by combining native capabilities with carefully selected third-party tools or custom development. Start with clear requirements definition, evaluate total cost of ownership including hidden costs, and maintain flexibility for future improvements. Most importantly, engage all stakeholders—from data engineers to security teams—early in the planning process to avoid costly surprises during implementation.
The investment in working around these limitations often pays dividends through improved data accessibility and business insights. However, success requires realistic expectations, appropriate tool selection, and ongoing optimization as both platforms evolve. By understanding and planning for these limitations, organizations can build robust integrations that deliver value despite current constraints.
