/
.webp)
Stacksync, Heroku Connect, and Workato offer solutions for data integration and synchronization. They approach pricing with distinct philosophies that significantly impact cost predictability, total cost of ownership (TCO), and platform suitability.
Stacksync presents a relatively transparent, tiered model primarily driven by the number of unique records synced. This approach decouples cost from update frequency. Heroku Connect utilizes an opaque, contract-based model for its paid tiers. It's tightly coupled with the Salesforce and Heroku ecosystems and heavily dependent on mandatory, potentially costly Heroku infrastructure components. Its core differentiator relates to Salesforce row limits for the free tier.
Workato employs a hybrid model combining a platform tier fee with usage-based charges driven by 'tasks' (workflow actions). This offers flexibility but requires careful monitoring for cost predictability.
Key differentiators emerge in transparency. Stacksync leads with publicly available pricing. Workato's model is described but requires sales contact for actual prices. Heroku Connect uses a contract-gated approach with minimal public pricing information.
The fundamental cost drivers diverge significantly. Stacksync focuses on data volume at rest. Heroku Connect centers on Salesforce integration within its ecosystem, implicitly tied to data scale but priced via contract. Workato charges based on workflow execution volume.
Platform dependencies are a major consideration. Heroku Connect has exclusive reliance on Heroku Postgres, creating significant vendor lock-in. Stacksync and Workato offer greater flexibility in integrating diverse environments.
Each platform aligns best with different use cases. Stacksync suits predictable, high-volume data synchronization. Heroku Connect targets deep Salesforce/Heroku integration within existing enterprise agreements. Workato caters to broad, complex business process automation across diverse applications.
Determining precise TCO presents challenges, especially for Heroku Connect and Workato. Opaque pricing elements, variable usage factors, and necessary infrastructure or add-on costs complicate accurate cost estimation.
The modern enterprise relies on a constellation of specialized applications. This creates an urgent need for robust solutions to synchronize and integrate data between systems like CRMs (e.g., Salesforce, Zoho CRM), databases (e.g., PostgreSQL, Snowflake, BigQuery), and various business applications.
Platforms like Stacksync, Heroku Connect, and Workato have emerged to address this challenge. They enable businesses to maintain data consistency, build integrated workflows, and leverage unified data across their operations.
Selecting the right platform is complicated by diverse and often complex pricing models. Decision-makers face significant hurdles in comparing costs and predicting TCO.
Heroku Connect offers limited public pricing information for its production tiers. This requires direct sales engagement and often bundling within larger contracts. Workato presents a multi-faceted model combining platform fees with task-based usage. Its final cost is typically determined through sales consultation.
Stacksync provides a more transparent tiered structure. However, understanding the nuances of its metrics and overage policies is still crucial. This lack of straightforward comparability makes objective evaluation difficult.
This report aims to demystify the pricing models of Stacksync, Heroku Connect, and Workato. It provides a detailed comparative analysis based on available official documentation and supplementary data.
The analysis examines the structure of each model, the core metrics driving costs, how costs scale with usage and features, potential additional or hidden costs, and the alignment of each model with typical business use cases and sizes.
The analysis relies primarily on official pricing pages and technical documentation provided by Stacksync, Heroku (for Heroku Connect), and Workato. Where official pricing details are incomplete or opaque, particularly for enterprise tiers or contract-based pricing, the report incorporates information from credible third-party analyses and user-reported data.
The goal is to present a factual, objective comparison of the pricing philosophies and their practical implications.
Official Pricing Source: The primary source for Stacksync's pricing is its official pricing page. It is worth noting that some third-party sources may reflect older pricing structures, so the official page should be considered authoritative.
Pricing Tiers and Base Costs: Stacksync offers a tiered subscription model with publicly listed prices for its initial plans:
Core Pricing Metrics: Pricing and feature access are differentiated across tiers based on several core metrics:
Synced Records: This is a primary cost driver. A record counts as "synced" if it's present at the start of the month or synced for the first time during the month. Importantly, Stacksync counts unique records across systems (no double counting) and allows unlimited updates to already-synced records without additional cost.
Limits: Starter (50,000), Pro (1 Million), Enterprise (Custom).
Active Syncs: An "active sync" represents a connection between two applications (e.g., Salesforce to Postgres). A sync counts as active when turned ON, regardless of the number of tables or fields mapped.
Limits: Starter (1), Pro (3), Enterprise (Unlimited).
Workflows: Automated processes built within Stacksync.
Limits: Starter (5), Pro (25), Enterprise (Unlimited).
Workflow Executions: The number of times workflows can run per month.
Limits: Starter (10,000), Pro (1 Million), Enterprise (Custom).
Managed Queues & Throughput: For managing asynchronous workflow executions.
Limits: Starter (1 queue, 1k events/min/queue), Pro (5 queues, 5k events/min/queue), Enterprise (Unlimited queues, 10M events/min/queue).
API Proxy Rate Limit: Limits on the usage of Stacksync's API proxy feature.
Limits: Starter (50,000 calls/day), Pro (150,000 calls/day), Enterprise (Unlimited).
Collaborators: Number of user seats per workspace.
Limits: Starter (3), Pro (Unlimited), Enterprise (Unlimited).
Other Differentiators: Tiers also vary by log retention (1, 7, or 30 days), number of environments (1 for Starter/Pro, 3 for Enterprise), support channels (Email only for Starter/Pro vs. Email, Slack, WhatsApp, Pagerduty for Enterprise), processing region options, and access to advanced features like compliance certifications (SOC2, ISO27k, HIPAA), Management API, Config as Code (Pro/Enterprise), MFA & SSO, dedicated solutions architects, and SLAs (Enterprise).
Model Structure: Stacksync employs a tiered subscription model. Each tier includes a base monthly fee covering the specified allowances for the metrics above. For synced records exceeding the plan limits, a pay-as-you-go component applies.
Costs scale primarily in two ways:
Tier Upgrades: Businesses requiring higher limits for synced records, active syncs, workflows, collaborators, or needing advanced features must upgrade to a higher tier.
Pay-as-you-go Overages: If the number of synced records exceeds the allowance in the Starter or Pro plan, overage charges apply based on a tiered structure that offers volume discounts.
50k - 150k records: $0.80 per additional thousand records/month
The Enterprise plan offers custom pricing, potentially including bulk volume discounts for very large-scale deployments. Additional Cost Considerations:
Stacksync stands out for its relative pricing transparency compared to the other platforms analyzed. The clear definition of tiers, included limits, and published overage rates allows organizations to estimate costs with reasonable accuracy based on their data volume.
A crucial aspect of the Stacksync model is that its primary cost scales with the volume of unique data records being managed. It does not scale with the frequency of updates or the complexity of individual workflows.
The explicit statement that unlimited updates are permitted for synced records without extra cost differentiates it significantly from task-based models. This structure directly supports Stacksync's focus on providing true bi-directional, real-time synchronization.
By charging per unique record rather than per update or sync operation, the model avoids penalizing high-velocity data environments. This potentially makes it more cost-effective for use cases involving frequent data changes on a relatively stable dataset.
Official Pricing Source: Information on Heroku Connect pricing is primarily found on the Heroku Elements add-on page and related developer documentation. A significant characteristic is the absence of explicit pricing details for its paid, production-ready tiers.
Pricing Tiers: Heroku Connect utilizes a freemium approach:
Demo Edition: This free tier is intended for evaluation and development purposes. It comes with significant limitations:
Paid Tiers (Shield, Enterprise): Accessing production capabilities requires a contract ("Enterprise Contract", "Shield Contract"). These tiers remove the 10,000-row limit, offering unlimited synchronized rows, and enable more frequent data polling (down to a 2-minute standard interval, plus 'accelerated polling' via Salesforce Streaming API for near real-time notifications). The Shield plan is specifically designed for use with Heroku Shield Private Spaces and Shield Heroku Postgres databases, catering to higher compliance needs.
Core Pricing Metrics: While the Demo plan is gated by a specific row count, the pricing for paid tiers is not directly based on per-row charges. Key factors influencing cost appear to be:
Model Structure: Heroku Connect employs a freemium model characterized by a functionally limited free tier and opaque, contract-based pricing for production usage. This lack of public pricing for paid tiers has been a point of frustration for potential users seeking clear cost comparisons.
Scaling costs with Heroku Connect involves several dimensions:
Additional Cost Considerations (Crucial for TCO): The cost of the Heroku Connect add-on itself is only one part of the equation. Several other factors significantly contribute to the TCO:
The most striking aspect of Heroku Connect's pricing is its opacity for production use. Costs are typically hidden within larger Heroku Enterprise or Salesforce contracts. This makes standalone evaluation and comparison difficult.
This model strongly favors organizations already heavily invested in the Salesforce and Heroku ecosystems. Connect is positioned as a native integration solution within that context.
The TCO potential for Heroku Connect can be significantly higher than the add-on fee alone might suggest. The mandatory use of specific, often high-tier, Heroku Postgres plans combined with the costs of Heroku Dynos to run the consuming applications creates substantial associated infrastructure expenses. This dependency represents a major component of the overall cost structure.
The strict requirement for Heroku Postgres introduces significant vendor lock-in. Organizations cannot use Heroku Connect with other database providers. This limits architectural flexibility and potentially hinders multi-cloud strategies.
While paid plans offer faster synchronization capabilities than the Demo tier, including accelerated polling, the underlying mechanism remains based on polling and streaming. This results in "eventual consistency" rather than guaranteed real-time updates.
Achieving performance that feels near real-time depends heavily on factors like data volume, change frequency, object complexity, database performance, and proper configuration. This implies a potential trade-off between desired sync speed and the cost of the required infrastructure and tuning effort.
Official Pricing Source: Workato describes its current pricing model, effective February 2024, in its official documentation. However, specific price points for platform tiers and task packages are generally not published online and require direct contact with their sales team.
The February 2024 model centers around three platform plans, differentiated by the level of capabilities they unlock:
Note on Historical/Third-Party Data: It's important to acknowledge that older documentation or third-party sources frequently reference different tier names (e.g., "Team," "Professional," "Unlimited" or "Premium," "Professional," "Enterprise") and provide various estimated price ranges. These estimates vary widely, from $10,000-$50,000+ per year, average contract values around $50,000, or monthly estimates starting from $2,000-$7,000+. One user report mentioned potential list prices for the newer tiers: Standard ($40k), Business ($70k), Enterprise ($100k). While these figures offer context on potential scale, the official Feb 2024 structure is the current framework, and definitive pricing requires a sales quote.
Core Pricing Metrics: Workato's pricing model (post-Feb 2024) has two primary components:
Model Structure: The model combines a recurring subscription fee (Platform Plan Fee) with a variable usage fee based on task consumption, adhering to a "pay for what you consume" principle.
Costs in the Workato model scale primarily through:
Additional Cost Considerations: Beyond the platform fee and task usage, several other elements can influence the TCO:
Workato's pricing model attempts to balance platform access with usage-based costs. The task metric provides flexibility, allowing costs to scale somewhat proportionally to actual automation activity.
However, this flexibility comes at the cost of predictability. Estimating task consumption accurately can be challenging, especially for new or evolving workflows. This makes budget forecasting less straightforward than fixed-tier models.
Continuous monitoring of task usage via the platform's dashboard is essential for cost management. The importance of optimization strategies is highlighted by the model itself.
Techniques like converting high-use workflows to HVRs, utilizing batch/bulk trigger and action steps where possible (processing 100 records as 1 task instead of 100 tasks), and adjusting polling intervals for non-critical recipes can significantly impact overall task consumption and cost.
This pricing structure supports Workato's positioning as a comprehensive enterprise automation platform. It encourages building a wide array of automations ("recipes") across various business functions, but ties the cost directly to the operational intensity and execution frequency ("tasks") of these automations.
The lack of public pricing and evidence from third-party sources strongly indicate that negotiation is a critical part of the procurement process. Reported discounts, waived fees, and adjustments to package inclusions suggest that the initial quote or list price is often a starting point, particularly for larger commitments.
Analyzing the pricing models of Stacksync, Heroku Connect, and Workato reveals fundamental differences. These differences impact what drives costs, how synchronization approaches affect pricing, the level of transparency offered, and the degree of platform dependency involved.
The most significant difference lies in the primary metric used to measure and charge for usage.
Stacksync costs primarily scale with the number of unique synced records. This represents the volume of distinct data entities being managed and kept in sync across connected systems.
Heroku Connect's free tier is limited by a Salesforce row count (10,000 rows). Paid tiers operate on a contract basis. Pricing isn't directly metered per row but is negotiated within the contract, likely influenced by the overall scale and the Heroku/Salesforce relationship.
Workato costs are driven by a combination of the chosen Platform Plan tier (unlocking features) and the number of tasks executed. This reflects the activity level and complexity of the automated workflows.
This divergence means that cost predictability varies significantly. Stacksync's record-based model offers high predictability based on data volume. Workato's task-based model makes costs dependent on workflow activity, which can fluctuate. Heroku Connect's contract-based model offers the least external predictability, requiring direct negotiation.
The way each platform handles data synchronization and how it's priced also differs.
Stacksync prices based on records, explicitly allowing unlimited updates without extra cost. This supports its real-time, bi-directional sync capability without penalizing high-frequency data changes. It makes Stacksync potentially cost-effective for dynamic datasets where the number of records is relatively stable.
Heroku Connect uses polling and Salesforce's Streaming API for eventual consistency. Faster polling capabilities (e.g., 2-minute intervals, accelerated polling) are features of the paid tiers. This means the capability for faster sync is tied to the contract cost, not directly metered per poll. However, achieving optimal performance requires sufficient underlying infrastructure (Postgres, Dynos), adding an indirect cost factor to sync speed.
Workato supports various trigger mechanisms including polling, real-time (often webhook-based with polling backup), scheduled, and Change Data Capture (CDC). Crucially, each trigger event and subsequent action step consumes tasks. Therefore, the frequency and method of synchronization directly impact task consumption and cost. Optimizing polling intervals or using efficient triggers like webhooks (where available and reliable) is key to managing costs.
The choice between near real-time needs and cost tolerance is framed differently by each platform. Stacksync decouples sync frequency from the primary cost metric. Workato directly links sync activity (polling checks, webhook triggers, workflow steps) to cost via tasks. Heroku Connect ties the ability to sync faster to its paid contract tiers, with performance also dependent on infrastructure investment.
The level of transparency and resulting cost predictability differs markedly.
Stacksync offers the highest transparency, with publicly listed prices for Starter and Pro tiers, clearly defined metrics, and published overage rates. This allows for relatively straightforward self-service cost estimation.
Heroku Connect exhibits very low transparency for its paid Shield and Enterprise plans, requiring sales contact and contract negotiation. While the costs of the required infrastructure (Heroku Postgres, Dynos) are predictable based on Heroku's standard pricing, the overall TCO, including the Connect fee itself, is difficult to predict without engaging Sales.
Workato provides moderate transparency by describing its pricing model structure (Platform + Tasks), but lacks public pricing for tiers and task packs. Predictability is moderate. While the model is known, actual costs depend on a sales quote and careful monitoring of variable task consumption.
Consequently, the ease of budgeting and performing initial comparative analysis varies greatly. Stacksync facilitates easier upfront estimation. Heroku Connect and Workato necessitate direct vendor engagement for accurate pricing.
The degree to which each platform requires commitment to a specific ecosystem varies.
Heroku Connect imposes the highest degree of lock-in by mandating the use of Heroku Postgres. It is fundamentally tied to the Heroku platform and designed for Salesforce integration within that context.
Stacksync and Workato exhibit lower inherent platform lock-in. Both are designed as integration platforms connecting a variety of external cloud applications and databases. Workato utilizes On-Premise Agents (OPAs) to facilitate connectivity with systems behind a corporate firewall, further extending its reach without tying users to a specific cloud infrastructure provider for the core service.
This means choosing Heroku Connect is a strategic commitment to the Heroku/Salesforce ecosystem. Stacksync and Workato offer greater flexibility in integrating diverse environments.
The distinct pricing models and technical characteristics of Stacksync, Heroku Connect, and Workato make them suitable for different use cases and imply varying Total Cost of Ownership (TCO) considerations.
Stacksync aligns best with scenarios where the primary need is robust, real-time, potentially bi-directional data synchronization between a defined set of core systems. This particularly applies to CRM and database pairings.
Its record-based pricing makes it cost-effective when dealing with high volumes of data updates on a relatively stable number of unique records. Organizations valuing cost predictability based on data volume, from startups to enterprises needing reliable core data sync, will find this model appealing.
Heroku Connect is specifically tailored for organizations deeply embedded in both the Salesforce CRM and Heroku Platform-as-a-Service (PaaS) ecosystems. It excels at providing seamless, point-and-click data integration between these two specific platforms.
Its contract-based pricing, often bundled within larger enterprise agreements, makes it most suitable for companies already operating under such arrangements. It is less appropriate for organizations seeking multi-cloud flexibility or needing to integrate systems outside the Heroku/Salesforce sphere.
Workato is ideally suited for organizations requiring a broad enterprise automation and integration platform (iPaaS) to connect a wide array of applications (cloud and potentially on-premise via OPAs). It excels at orchestrating complex, multi-step business processes across various departments (e.g., IT, HR, Finance, Sales, Marketing, Support).
Its task-based pricing aligns with use cases where the value is derived from the volume and complexity of automated workflows, rather than just data synchronization volume. Businesses needing extensive workflow orchestration, API management, and process automation beyond simple data mirroring will leverage Workato's strengths.
Calculating the true TCO requires looking beyond the base subscription or license fees. Key components include:
Base fees represent the recurring subscription costs for Stacksync tiers, the platform fees for Workato tiers, and the negotiated contract value for Heroku Connect (often bundled).
Usage costs include overage charges for synced records in Stacksync, task consumption costs (including potential overages beyond purchased packs) in Workato, and any implicit scaling factors within Heroku Connect contracts.
Infrastructure costs are a major differentiator. Heroku Connect mandates potentially expensive Heroku Postgres plans and associated Heroku Dynos. Workato may require costs associated with On-Premise Agents (OPAs) for hybrid scenarios. Stacksync, being a SaaS platform connecting external systems, imposes minimal direct infrastructure costs on the user beyond the systems being connected.
Add-on features include costs for additional user seats (Workato, potentially Stacksync Starter), increased concurrency (Workato), premium support tiers, or potentially specialized connectors (Workato).
Implementation and professional services cover costs associated with initial setup, data migration, custom workflow development, integration tuning, and user training. These can vary significantly based on complexity and may involve vendor services or third-party consultants.
Support costs represent ongoing costs for desired support levels beyond what is included in the base plan.
Contract terms include factors like minimum commitment periods (often annual for Workato/Heroku Enterprise), payment frequency, and renewal uplift clauses that impact long-term costs.
Understanding these components reveals that TCO is multi-faceted. Heroku Connect's TCO is heavily influenced by its mandatory infrastructure dependencies. Workato's TCO is sensitive to actual workflow usage volume and the potential need for various add-ons and higher support tiers. Stacksync's TCO appears more directly correlated with the volume of data being managed, offering potentially greater predictability if data volumes are known.
The analysis highlights stark contrasts between Stacksync, Heroku Connect, and Workato.
Stacksync offers transparent, record-based pricing suited for predictable data synchronization. Heroku Connect provides opaque, contract-based pricing deeply integrated with, and dependent upon, the Salesforce/Heroku ecosystem. It prioritizes seamless integration over transparency or flexibility.
Workato employs a flexible but less predictable task-based model combined with platform tiers. It targets broad enterprise automation and requires usage monitoring and optimization for cost control.
Trade-offs exist across predictability, flexibility, platform lock-in, and alignment with specific integration versus broader automation goals.
Clearly determine if the core requirement is primarily data synchronization between specific systems (favors Stacksync/Heroku Connect focus) or broad-based business process automation across many applications (favors Workato focus).
Attempt to quantify the relevant metrics for each platform.
For Stacksync, estimate the number of unique records (e.g., contacts, accounts, orders) that need to be kept in sync.
For Heroku Connect, determine the total number of Salesforce rows across objects to be synced (to assess Demo plan viability) and understand the existing or planned Heroku/Salesforce expenditure.
For Workato, estimate the anticipated volume of workflow executions (recipes running) and the average number of steps (tasks) per execution. This is often the hardest to predict accurately upfront.
Due to the opacity or variability, engage directly with sales teams, especially for Workato and Heroku Connect. Ensure quotes detail all potential costs, including:
Evaluate the business need for real-time versus eventually consistent data. Understand how each platform's model supports and charges for the required level of freshness.
Stacksync's model is inherently friendly to high frequency. Workato's cost scales with frequency. Heroku Connect's capability scales with tier/contract.
Consider the internal expertise required versus the potential need for professional services. Evaluate the long-term cost and value of different support plan levels.
For Heroku Connect, critically assess the organization's long-term commitment to using Heroku PaaS and Heroku Postgres, given the inherent lock-in.
If considering Workato, plan for initial close monitoring of task consumption to understand real-world usage patterns and optimize workflows for cost-efficiency early on. Consider piloting key workflows to establish baseline task usage.
Stacksync, Heroku Connect, and Workato employ fundamentally different pricing strategies. Each reflects distinct platform philosophies and target use cases.
Stacksync offers transparency and predictability tied to data volume. Heroku Connect prioritizes deep integration within the Salesforce/Heroku ecosystem, with opaque pricing and significant infrastructure dependencies. Workato provides a flexible, task-based model for broad automation, trading some predictability for usage-based scaling.
There is no single "best" pricing model. The optimal choice depends on your organization's specific technical requirements, usage patterns, tolerance for cost variability, and existing technology investments.
A thorough evaluation must extend beyond surface-level features. Consider the nuances of each pricing model, potential hidden costs, platform dependencies, and long-term TCO implications. Direct engagement with vendors to obtain detailed, tailored quotes reflecting your full scope of requirements is essential for making an informed decision.
Ready to find the right pricing model for your data integration needs? Explore how Stacksync works to understand transparent, predictable pricing that scales with your data volume without penalizing high-frequency updates.
