2025 No-Code Infrastructure Cost Benchmark Report: Bubble vs. Momen

Executive Summary: The Strategic Calculus of No-Code Platform Selection

This report presents a comparative cost analysis of two prominent no-code development platforms: Bubble and Momen. As the no-code movement continues to mature, understanding the long-term operational costs of these platforms has become a key consideration for founders, product managers, and technical stakeholders.

Using a standardized modeling framework, we estimate the monthly infrastructure costs for nine common application archetypes — including B2B SaaS, E-commerce, EdTech, and Social Networks — based on publicly available pricing, platform documentation, and consistent assumptions around usage patterns, file storage, and compute intensity.

Our analysis highlights how each platform approaches pricing differently:

• Bubble uses a usage-based model where cost scales with server-side operations (measured in Workload Units), offering flexibility but introducing variability.

• Momen employs a bundled resource model with fixed limits and upgrade paths based on performance thresholds (measured in Requests Per Second), emphasizing predictability.

While the results show significant cost differences across archetypes, the optimal platform depends heavily on the specific demands of the application and the organization’s tolerance for usage-based pricing. This report is intended to support more informed platform selection by offering:

• A consistent framework for forecasting monthly infrastructure costs

• Detailed cost breakdowns across representative app types

• A discussion of trade-offs between pricing models, performance ceilings, and scalability

Whether you're evaluating a platform for an internal tool or a large-scale production app, this benchmark aims to clarify the financial implications of your no-code infrastructure decisions.

Table ES-1: Summary of Estimated Monthly Costs (Bubble vs. Momen)

Section 1: Deconstructing the Pricing Philosophies: Bubble vs. Momen

Understanding the estimated costs of building and scaling an application on a no-code platform requires a deep dive into the core economic models that govern each provider. Bubble and Momen, while both enabling powerful application development without code, operate on fundamentally different pricing philosophies. Bubble employs a metered, usage-based system centered on an abstract unit of consumption, while Momen utilizes a more predictable, bundled-resource model. This foundational difference has profound implications for budget forecasting, risk management, and strategic platform selection.

The Bubble Paradigm: Metered Usage and the Enigma of Workload Units (WU)

Bubble's pricing structure is designed to scale directly with application usage, tying costs closely to the server resources consumed. This model offers immense flexibility but introduces a significant degree of complexity and potential for cost volatility.

Core Pricing Structure: Bubble offers several paid tiers, with monthly billing options for its Starter ($32/month), Growth ($134/month), and Team ($399/month) plans.4 These plans serve as the entry point, providing a base set of features and an initial allocation of server resources. While annual billing offers a discount, the monthly rates are used here for direct comparison.6

The Workload Unit (WU) Explained: The central metric in Bubble's pricing is the Workload Unit (WU). It is a proprietary, aggregated measure of the server resources your application consumes.6 Instead of billing separately for CPU cycles, database reads/writes, and other traditional server metrics, Bubble bundles them into this single unit. Every server-side action—from a user logging in, to a database query being executed, to a workflow running, to an API call being made—consumes a specific amount of WU.7 This abstraction simplifies resource monitoring to a single metric but simultaneously obscures the direct cost of any given feature or user action.

WU Allocations and Overages: Each paid plan includes a monthly allotment of WU: 175,000 for the Starter plan, 250,000 for Growth, and 500,000 for Team.5 These allowances are sufficient for applications in early development or with modest user bases. However, as an application scales, it will inevitably exceed these limits. This is where Bubble's primary scaling cost becomes apparent. Any usage beyond the plan's allowance is billed as an overage at a rate of $0.30 per 1,000 WU.4 For applications with predictable, sustained usage above their plan's limit, Bubble offers dedicated "workload tiers," such as an additional 200,000 WU for a fixed $29 per month, which is a more economical option than paying for overages on a per-unit basis.9

The User Sentiment & Predictability Problem: The abstract nature of the WU has led to significant concern within the Bubble developer community regarding cost predictability. Forum discussions reveal a pattern of users launching applications only to find their actual monthly costs are orders of magnitude higher than anticipated.2 Users have described Bubble's own cost-estimation tools as "dangerously inaccurate and misleading," citing examples of social network applications projected to cost under $100 per month but realistically consuming millions of WU and incurring costs of many hundreds or thousands of dollars, even with a small user base. This documented user experience underscores the critical risk associated with the WU model: the potential for unexpected and dramatic budget overruns.

Ancillary Cost Vectors: Beyond the base plan and workload, several other factors can contribute to the total monthly cost:

• File Storage: While plans include some storage, additional capacity is priced at $3 per 100 GB per month.7

• Bandwidth: Each plan has a generous but finite monthly bandwidth limit (e.g., 100 GB for Starter, 500 GB for Growth).7 Exceeding this could lead to performance throttling or require a plan upgrade.

• Plugins: The extensive plugin marketplace is a core strength of Bubble, but many powerful plugins are not free. They can require one-time payments or, more commonly, ongoing monthly subscriptions, adding a variable and often overlooked layer to the total cost of ownership.7

The Momen Approach: Bundled Resources and A La Carte Expansion

Momen positions itself with a pricing philosophy centered on predictability and transparency, a direct counterpoint to the potential volatility of metered models like Bubble's.10 Its structure is designed to provide clear, upfront cost estimates by bundling resources into its plans and offering itemized pricing for expansion.

Core Pricing Structure: Momen's pricing is organized on a per-project basis, with its primary paid plans being the Basic plan ($39/month) and the Pro plan ($99/month).12 This per-project model is a key distinction from Bubble's account-level plans, which can host multiple applications.

The Cloud Resource Unit (CRU) Deconstructed: Momen's equivalent to the WU is the Cloud Resource Unit (CRU), but it functions very differently. A CRU is not an abstract measure of computation but a specific, defined bundle of resources. According to Momen's pricing documentation, 1 CRU consists of: 200 MB of object storage, 200 MB of data outflow per month, 1,000 Actionflow automations per month, 20 MB of database storage, and 100,000 AI Points.3 This concrete definition removes ambiguity and allows for direct calculation of a plan's capacity.

A Critical Distinction in Compute Costs: A crucial detail of Momen's pricing is that the "Actionflow Automation Count" is a billable metric that applies only to workflows triggered by backend events, such as database triggers or scheduled jobs. However, this does not mean other operations are free. All frontend-triggered workflows and direct database operations (Create, Update, Delete) are governed by a hard Requests Per Second (RPS) limit on each plan: 5 RPS for the Basic plan and 25 RPS for the Pro plan.12

CRU Allocations: The Basic plan includes 10 CRUs, and the Pro plan includes 50 CRUs.12 This means a customer on the Pro plan receives a monthly allowance of 1 GB of database storage ( 50×20 MB), 10 GB of object storage (50×200 MB), 10 GB of data outflow, and 50,000 billable Actionflow automations (50×1000) as part of their fixed $99 fee.

The "Predictable Cost" Value Proposition: Momen heavily markets its "Predictable Cost" model, emphasizing that there are "no additional charges for database, Actionflow, or API utilization" within the plan's limits.10 This approach, combined with the RPS ceiling, creates a predictable cost structure. If an application's peak traffic exceeds the RPS limit of the Pro plan, the upgrade path is not to a more expensive usage-based tier, but to a fixed-cost "Single Tenant Kit" with no RPS limits.3

A La Carte Add-ons: When an application's needs exceed the bundled resources, Momen provides a transparent, a la carte menu of add-ons for scaling. This is a critical element of its model. The costs are clearly defined 3:

• Database Storage: $100 per 1 GB per year, which translates to $8.33 per GB per month.

• Object Storage: $35 per 100 GB per year, or $2.92 per 100 GB per month.

• Outflow Bandwidth: $35 per 500 GB.

• Actionflow Automations: $10 per 100,000 executions.

This itemized pricing for specific resource dimensions allows for precise cost control and forecasting as an application grows.

A Philosophical Divide in Risk and Strategy

The contrasting pricing models of Bubble and Momen reflect a deeper, philosophical split in how operational and financial risk is allocated between the platform and its customers. This difference is central to making a strategic choice between them.

Bubble's pure usage-based model places the majority of the operational risk directly on the customer. Every server-side activity, from an inefficiently designed database query to an unexpected surge in viral traffic, has a direct and immediate cost in the form of WU consumption.7 While this provides a mechanism for infinite, granular scaling, it means the customer's monthly bill is subject to the inherent volatility of user behavior and the technical efficiency of their application build. The platform's revenue scales with this usage, while the customer bears the financial consequences of any deviation from the forecast.

Momen's bundled-resource model, by contrast, shifts a significant portion of this initial risk to the platform. By including a substantial buffer of resources and establishing a hard performance ceiling (RPS) on its shared plans, Momen guarantees a fixed cost.12 The risk of a surprise bill from a usage spike is eliminated. Instead, the risk becomes one of performance; if traffic exceeds the plan's RPS limit, the application's performance may degrade until it is upgraded. The upgrade path for high-traffic applications is to the "Single Tenant Kit," a fixed-price dedicated plan that removes the RPS limit and offers unlimited Actionflow automations, providing ultimate cost predictability at scale.3

This division creates two distinct ideal customer profiles. Bubble is well-suited for ventures with strong technical leadership capable of rigorously optimizing their application for the WU system, as detailed in various optimization guides.8 It is also viable for well-funded startups that can absorb potential cost volatility in exchange for a high-ceiling scaling path, a reality alluded to by users who note the need for VC funding to afford scaling on the platform.2 Momen, on the other hand, is a more natural fit for bootstrapped startups, small-to-medium-sized businesses, or agencies building client applications, where budget predictability is paramount for financial planning and risk mitigation. The decision is therefore not simply a technical one, but a core strategic choice about the business's tolerance for financial uncertainty.

Section 2: Analytical Framework and Core Modeling Assumptions

To provide a credible and transparent comparison of monthly costs, it is essential to establish a rigorous analytical framework. This framework must bridge the gap between the generic application metrics provided 1 and the specific, proprietary pricing models of Bubble and Momen. The following section details the formulas, conversions, and critical assumptions used to model resource consumption and calculate estimated costs. The explicit declaration of these assumptions is paramount, as the final cost estimates are highly sensitive to these modeling decisions.

Calculating Foundational Resource Requirements (The Knowns)

The first step is to convert the raw data for each application archetype into standardized monthly consumption figures for storage and bandwidth. These calculations form the baseline resource footprint of each application.

Database Size (GB): The total size of the application's database is a primary cost driver, particularly for Momen. The calculation accounts for the size of the main tables, extrapolates to the full database, and applies a bloat factor for overhead like indexes.

• Formula: $Total\ DB\ Size\ (GB) = \frac{(\sum (Row\ Count \times Avg.\ Row\ Size)) / Estimated\ % \ of\ Total\ DB\ Space \times Bloat\ Factor}{1024^3}$

• Explanation: The formula first sums the size of the top five database tables provided for each archetype. This sum is then divided by the estimated percentage of total database space that these tables represent (e.g., divided by 0.85 for a B2B SaaS app where the top tables constitute 85% of the database) to estimate the total size of all data rows. This figure is then multiplied by the Bloat Factor to account for database indexes, metadata, and other operational overhead that consumes disk space but is not part of the raw data itself. The final result is converted from bytes to gigabytes.1

Object Storage (GB): This metric represents the cumulative storage required for user-generated media and files, such as images, videos, and documents. For this analysis, the cost is modeled based on the storage required for one month's worth of new uploads, representing the marginal cost of growth.

• Formula: Monthly Object Storage Growth (GB)=10243DAU×30×∑(Media per DAU×Avg. Media Size)​

• Explanation: This formula calculates the total volume of new files uploaded per month. It multiplies the Daily Active Users (DAU) by 30 to get a monthly user activity baseline. This is then multiplied by the sum of all media types (images, videos, files) uploaded per DAU per day, each weighted by its average size. The result is the total new storage in gigabytes consumed each month.1

Data Outflow/Bandwidth (GB): Data outflow, or bandwidth, is the amount of data sent from the application's servers to its users. This is primarily driven by the viewing and downloading of stored media and files.

• Formula: Monthly Data Outflow (GB)=Monthly Object Storage Growth (GB)

• Explanation: To create a conservative and reasonable estimate, this model makes the simplifying assumption that, on average, every file uploaded in a given month is also accessed (viewed or downloaded) at least once. Therefore, the monthly data outflow is assumed to be equal to the monthly growth in object storage. This value can be directly compared to Momen's Outflow Bandwidth add-on pricing 3 and the monthly allowances included in Bubble's plans.7

Modeling Compute Consumption (The Great Unknown)

The most challenging aspect of this analysis is modeling the computational load, as the "Ops/Sec" metric is generic and does not directly map to either platform's proprietary units. The following models represent expert estimations based on available documentation and are the most critical assumptions in this report.

Proposed Model for Bubble Workload Units (WU):

• Formula: Total Monthly WU=(DAU×Ops/Sec×86,400×30)×WUp​erO​perationF​actor

• Assumption: The WU_per_Operation_Factor is set to 0.6.

• Justification: A direct, official conversion from a generic "operation" to Bubble's WU does not exist. The Ops/Sec metric represents an amalgamation of various server-side actions. An analysis of Bubble's own documentation reveals the cost of atomic components of an operation: a basic database search (Do a search for) has a starting cost of 0.3 WU, and an aggregation (like a count or average) costs a base of 0.2 WU, with additional costs for the amount of data transferred.13 A database write or modification action also consumes WU. A typical user-facing "operation" is rarely a single atomic action but rather a workflow composed of multiple steps: reading data, evaluating a condition, and writing a result. Therefore, a 1:1 mapping would be overly optimistic. The chosen factor of 0.6 is a conservative estimate that models a hypothetical "average operation" as consisting of one database read (approx. 0.3 WU), one database write (estimated at 0.2 WU), and a small amount of associated logic or data transfer (estimated at 0.1 WU). This factor is intentionally set to be realistic rather than perfectly optimal, acknowledging the widespread community feedback on unexpectedly high WU consumption 2 and the numerous optimization guides that highlight how easily unoptimized actions can multiply costs.8 This assumption is the single most significant variable in the Bubble cost estimation.

Proposed Model for Momen Actionflow Automations and Performance Limits:

• Billable Actionflows Formula: Total Monthly Billable Actionflows=(DAU×Ops/Sec×86,400×30)×BillableO​psF​actor

• Billable Actionflows Assumption: A Billable_Ops_Factor of 10% is applied to the total estimated operations.

• Justification: Momen's pricing model for compute is highly specific: only Actionflows triggered by backend events (database triggers and scheduled jobs) are counted and billed. In most applications, these represent a fraction of total operations. This model assumes 10% of the generic "Ops/Sec" fall into this billable category.

• Peak RPS Formula: Peak RPS=(DAU×Peak Ratio)×Ops/Sec

• Peak RPS Assumption: This formula models the peak requests per second, which determines if an application can run on Momen's shared plans. It assumes Ops/Sec is per-user and Peak Ratio is the percentage of daily users active at the busiest moment.1

• Implication: Momen's plans have hard RPS limits: 5 RPS for Basic and 25 RPS for Pro.12 If an application's calculated
  Peak RPS exceeds 25, it is assumed to require the Single Tenant Kit ($120/month), which offers no RPS limit and unlimited Actionflow automations.3 This is a critical constraint that dictates the entire cost structure for high-traffic applications on Momen.

Hidden Cost Floors and Strategic Plan Selection

A purely resource-based analysis can be misleading because the "cheapest" plan is not always the "correct" or even a viable plan. Business and security requirements often dictate a higher starting tier, creating a non-negotiable floor on the monthly cost, regardless of initial usage levels.

This analysis reveals that a crucial factor in plan selection is the availability of enterprise-grade features. For instance, Bubble's feature comparison shows that Two-Factor Authentication (2FA), a common security requirement for any application handling sensitive user data, is only available on the Growth plan ($134/month) and higher.5 Similarly, Momen's documentation indicates that features like Single Sign-On (SSO) and advanced, role-based Permission Control are exclusive to the Pro plan ($99/month) and higher.12

Furthermore, Momen's RPS limits introduce a performance-based cost floor. Any application whose peak operational load exceeds 25 RPS is assumed to be non-performant on the shared Pro plan, making the fixed-cost Single Tenant Kit the mandatory choice.3

For application archetypes such as B2B SaaS, Fintech, or Healthcare, these features are not optional luxuries; they are mandatory requirements for meeting customer expectations, achieving compliance (e.g., SOC 2, HIPAA), and ensuring data security. Consequently, for these archetypes, the analysis will not select the cheapest possible plan based on resource consumption alone. Instead, it will select the lowest-tier plan that provides these essential features or performance capabilities. This insight fundamentally alters the cost equation for several archetypes, revealing a hidden cost floor dictated by business, security, and performance needs, not just by technical consumption.

Section 3: Granular Cost Analysis by Application Archetype

This section applies the analytical framework and assumptions detailed previously to each of the nine application archetypes. For each archetype, a resource profile is calculated, followed by a detailed, itemized cost estimation for both Bubble and Momen. This granular breakdown reveals the specific cost drivers for each scenario and platform.

B2B SaaS

A typical B2B SaaS application is characterized by moderate user counts but complex, data-intensive workflows, such as task and project management. Data security and integration capabilities like SSO are often paramount.

Resource Profile Calculation

With a DAU of 1,000, this archetype generates a significant number of database operations related to tasks and comments, and a substantial volume of file uploads, but has a relatively small core database size.

Table 3.1.A: B2B SaaS - Calculated Monthly Resource Requirements

Bubble Estimated Monthly Cost

For a B2B SaaS, features like 2-Factor Authentication are critical, mandating the selection of the Growth Plan ($134/month) as the minimum viable tier.5 The application's high operational load results in WU consumption that vastly exceeds the plan's allowance, making overages the dominant cost factor.

Table 3.1.B: Bubble Cost Breakdown for B2B SaaS

Momen Estimated Monthly Cost

For a B2B SaaS application, opting for the Single Tenant Kit ($120/month) provides ultimate cost predictability.3 Although the application's peak RPS of 7.5 is within the Pro plan's limits, the Single Tenant Kit eliminates all variable costs associated with Actionflow automations, as it includes unlimited compute.3 This makes it a strategic choice for applications with high operational loads.

Table 3.1.C: Momen Cost Breakdown for B2B SaaS

Archetype-Specific Analysis

For the B2B SaaS archetype, the defining characteristic is an extremely high ratio of computational operations to users. On Bubble, this translates to massive WU overage costs. By opting for Momen's Single Tenant Kit, the variable cost of compute is completely eliminated in favor of a fixed monthly fee. This strategic plan selection makes Momen's cost profile exceptionally predictable and significantly lower than Bubble's.

E-commerce Marketplace

An E-commerce Marketplace is defined by a large, fixed product catalog, a high number of users, and transaction-oriented workflows (orders, messages, reviews). It is also storage-intensive due to product imagery.

Resource Profile Calculation

With 5,000 DAU, this archetype has a large database dominated by a fixed product table. It generates a high volume of media uploads and a correspondingly high number of operations.

Table 3.2.A: E-commerce Marketplace - Calculated Monthly Resource Requirements

Bubble Estimated Monthly Cost

Given the consumer-facing nature and complexity, the Growth Plan ($134/month) is the appropriate starting point. The combination of high DAU and moderate operational intensity per user leads to massive WU consumption, making overages the primary expense. The significant object storage requirement also necessitates purchasing additional storage.

Table 3.2.B: Bubble Cost Breakdown for E-commerce Marketplace

Momen Estimated Monthly Cost

The calculated Peak RPS of 50 exceeds the Pro plan's 25 RPS limit, making the Single Tenant Kit ($120/month) the only viable option.3 This plan includes generous resource allowances and no limit on Actionflow automations, resulting in a highly predictable and low cost.

Table 3.2.C: Momen Cost Breakdown for E-commerce Marketplace

Archetype-Specific Analysis

The E-commerce Marketplace's high traffic pushes it beyond Momen's shared plan limits. This triggers an upgrade to the Single Tenant Kit, which, due to its fixed-price, all-inclusive nature for compute, becomes extraordinarily cost-effective compared to Bubble's usage-based model. The cost on Bubble is driven by WU overages, while the cost on Momen is a predictable flat fee plus minor storage and bandwidth overages.

Social Network / Community

This archetype is defined by exponential data growth, particularly in relational data like follows and likes, and a very high computational load per user. It is also extremely storage-intensive due to user-uploaded images and videos.

Resource Profile Calculation

At 10,000 DAU and a high Ops/Sec rate of 0.2, this is the most resource-intensive archetype. It generates an enormous database and a massive volume of media, leading to extreme compute and storage requirements.

Table 3.3.A: Social Network - Calculated Monthly Resource Requirements

Bubble Estimated Monthly Cost

For a high-traffic, scaling application like a social network, the Team Plan ($399/month) is the only logical choice, offering the highest base WU and bandwidth. Even so, the calculated WU consumption is staggering, leading to astronomical overage costs. The large database and massive file storage also contribute significantly to the total cost.

Table 3.3.B: Bubble Cost Breakdown for Social Network

Momen Estimated Monthly Cost

With a Peak RPS of 300, the Social Network far exceeds the Pro plan's limit, mandating the Single Tenant Kit ($120/month).3 This plan's unlimited compute and generous storage allowances make it the only feasible option, resulting in a dramatically lower cost.

Table 3.3.C: Momen Cost Breakdown for Social Network

Archetype-Specific Analysis

The Social Network represents a stress test for any platform's scaling model. On Bubble, the cost is astronomical and almost entirely composed of variable WU overages. On Momen, the high RPS forces an upgrade to the predictable, fixed-cost Single Tenant Kit. This results in a cost that is less than 0.1% of Bubble's estimate, making it the only financially viable platform of the two for this archetype.

Content Platform (Blog/News)

This archetype is characterized by a relatively low operational load per user, as most users are consuming content rather than creating it. The database contains large, but relatively static, tables for articles and comments.

Resource Profile Calculation

With 2,000 DAU and a low Ops/Sec of 0.05, the computational load is moderate. The primary storage driver is images and some video associated with articles.

Table 3.4.A: Content Platform - Calculated Monthly Resource Requirements

Bubble Estimated Monthly Cost

The Growth Plan ($134/month) is suitable for a platform of this scale. While the operational load is lower than other archetypes, it still generates enough WU to result in significant overage charges, which form the bulk of the cost.

Table 3.4.B: Bubble Cost Breakdown for Content Platform

Momen Estimated Monthly Cost

The Single Tenant Kit ($120/month) is selected as a strategic choice. Although the Peak RPS of 8 is within the Pro plan's limits, the high cost of Actionflow automations on the Pro plan makes the fixed-cost Single Tenant Kit, with its unlimited compute, a more economical and predictable option.3

Table 3.4.C: Momen Cost Breakdown for Content Platform

Archetype-Specific Analysis

For a content-focused platform, the high volume of backend processes would lead to significant variable costs on Momen's Pro plan. By strategically opting for the Single Tenant Kit, these variable compute costs are eliminated in favor of a predictable flat fee, making it vastly more affordable than Bubble's usage-based model.

Internal Tool

Internal tools typically have a very low user count (DAU of 200) but can be operationally intensive, with high-frequency logging and data entry. File storage needs can be significant if they are used for document management.

Resource Profile Calculation

Despite the low DAU, the high multiplier for logs and data entries (20x and 5x DAU respectively) and the large number of files per user (5) create a surprisingly demanding resource profile.

Table 3.5.A: Internal Tool - Calculated Monthly Resource Requirements

Bubble Estimated Monthly Cost

For a simple internal tool, the Starter Plan ($32/month) is sufficient. The operational load, while high per user, results in a total WU consumption that is manageable. The cost is primarily driven by WU overages, but at a much smaller scale than previous archetypes.

Table 3.5.B: Bubble Cost Breakdown for Internal Tool

Momen Estimated Monthly Cost

With a Peak RPS of only 0.6, the Basic Plan ($39/month) is more than sufficient.3 Its included resources are small, necessitating a few add-ons, but the total cost remains very low.

Table 3.5.C: Momen Cost Breakdown for Internal Tool

Archetype-Specific Analysis

Even for a low-DAU internal tool, Bubble's WU overage costs are significant. Momen's low traffic keeps it comfortably on the Basic plan, resulting in a much more economical and predictable monthly cost.

Fintech / Neobank

Fintech applications are defined by an extremely high volume of transactions per user and stringent security requirements. File storage needs are typically low, but database performance and integrity are critical.

Resource Profile Calculation

At 1,000 DAU, the standout metric is the 33 transactions per DAU, leading to a massive database write load and high Ops/Sec, mirroring the B2B SaaS case.

Table 3.6.A: Fintech / Neobank - Calculated Monthly Resource Requirements

Bubble Estimated Monthly Cost

Due to security needs (2FA), the Growth Plan ($134/month) is the mandatory minimum. The WU consumption is identical to the B2B SaaS case, resulting in massive overage costs that dwarf the base plan fee.

Table 3.6.B: Bubble Cost Breakdown for Fintech / Neobank

Momen Estimated Monthly Cost

The Single Tenant Kit ($120/month) is selected as the most cost-effective option. While the Peak RPS of 7.5 is within the Pro plan's limits, the extremely high cost of Actionflow automations for transaction processing makes the fixed-cost Single Tenant Kit a more logical and predictable choice.3

Table 3.6.C: Momen Cost Breakdown for Fintech / Neobank

Archetype-Specific Analysis

The Fintech archetype is compute-dominant. On Bubble, this leads to extreme costs. On Momen, strategically choosing the Single Tenant Kit eliminates all variable compute costs, resulting in a fixed, predictable, and exceptionally low monthly fee, making it the superior choice.

EdTech / Online Courses

EdTech platforms are uniquely characterized by extremely large file sizes, particularly for video course content. They also have high operational loads from progress tracking for many students.

Resource Profile Calculation

With 2,500 DAU, the platform's most notable feature is the 0.2 videos per DAU at a massive 200 MB average size. This results in an enormous monthly growth in object storage. The 44 progress tracking entries per DAU also create a significant compute load.

Table 3.7.A: EdTech - Calculated Monthly Resource Requirements

Bubble Estimated Monthly Cost

The Growth Plan ($134/month) is appropriate. The cost is driven by two major factors: the significant WU overages from progress tracking and, uniquely for this archetype, a very large bill for additional file storage.

Table 3.7.B: Bubble Cost Breakdown for EdTech

Momen Estimated Monthly Cost

The Single Tenant Kit ($120/month) is selected. Although the Peak RPS of 25 is at the Pro plan's limit, the high cost of Actionflow automations and the massive storage requirements make the Single Tenant Kit a more prudent and cost-effective choice, offering unlimited compute and larger base storage allowances.3

Table 3.7.C: Momen Cost Breakdown for EdTech

Archetype-Specific Analysis

The EdTech platform is a storage-dominant archetype with high compute needs. While Bubble's cost is driven by both WU overages and storage fees, Momen's cost, when using the Single Tenant Kit, is composed of a flat fee plus predictable storage and bandwidth overages, making it dramatically more affordable.

Healthcare / Telemedicine

Healthcare applications are defined by low user volume but extremely high-stakes data, with large file sizes for documents and notes. Security and compliance are the absolute top priorities.

Resource Profile Calculation

At only 500 DAU, the user base is small. However, the high Ops/Sec of 0.2 and the large file sizes (5 files at 2000 KB each) create significant compute and storage loads relative to the user count.

Table 3.8.A: Healthcare - Calculated Monthly Resource Requirements

Bubble Estimated Monthly Cost

For any healthcare application, the security features of the Growth Plan ($134/month) are non-negotiable. The high operational intensity per user results in substantial WU overages, which constitute the majority of the cost.

Table 3.8.B: Bubble Cost Breakdown for Healthcare

Momen Estimated Monthly Cost

The Single Tenant Kit ($120/month) is chosen for cost predictability. Despite a low Peak RPS of 4, the high cost of backend automations on the Pro plan makes the fixed-cost Single Tenant Kit a more financially sound option.3

Table 3.8.C: Momen Cost Breakdown for Healthcare

Archetype-Specific Analysis

The Healthcare archetype highlights the impact of strategic plan selection. Despite low traffic, choosing Momen's Single Tenant Kit to preemptively handle high backend automation costs results in a predictable, low monthly fee. This contrasts with Bubble's model, where costs remain high and variable due to WU consumption.

Job Board / Recruitment

A job board is a two-sided marketplace characterized by a very large user base, a large central database of jobs, and extremely high messaging volume between recruiters and candidates.

Resource Profile Calculation

With 8,000 DAU, this archetype has a high user count. The key drivers are the 11 messages and 5.5 applications per DAU, which create a massive database and computational load.

Table 3.9.A: Job Board - Calculated Monthly Resource Requirements

Bubble Estimated Monthly Cost

Given the scale and traffic, the Team Plan ($399/month) is the only appropriate choice. The WU consumption is immense, driven by the high volume of messages and applications. This results in very large overage costs.

Table 3.9.B: Bubble Cost Breakdown for Job Board

Momen Estimated Monthly Cost

A Peak RPS of 96 makes the Single Tenant Kit ($120/month) the mandatory choice, as it far exceeds the Pro plan's 25 RPS limit.3 The kit's unlimited compute and bundled resources make the total cost exceptionally low compared to the alternative.

Table 3.9.C: Momen Cost Breakdown for Job Board

Archetype-Specific Analysis

Like the Social Network, the Job Board is a compute-dominant application at scale. On Bubble, this leads to an extremely high monthly bill. On Momen, the high peak traffic forces an upgrade to the fixed-cost Single Tenant Kit, which provides unlimited compute for a flat fee, making it profoundly more affordable and predictable.

Section 4: Strategic Insights and Comparative Recommendations

The granular analysis of each application archetype provides the foundation for a higher-level strategic comparison. The data reveals clear patterns in cost structure, risk profile, and platform suitability. This section synthesizes these findings into a holistic view, offering a decision-making framework for selecting the most appropriate no-code platform based on an application's technical profile and the business's financial strategy.

The Complete Cost Landscape: A Cross-Archetype Comparison

Aggregating the results from Section 3 provides a stark, at-a-glance comparison of the total estimated monthly costs across all nine archetypes. The data, updated to reflect Momen's RPS limits and the availability of its Single Tenant Kit, shows that Momen's pricing model results in a dramatically lower total cost across every single modeled scenario.

Table 4.A: Summary of Estimated Monthly Costs (Bubble vs. Momen)

The Predictability vs. Granularity Trade-off Revisited

The concrete data from the analysis validates the initial thesis, but with a much sharper conclusion: the choice between Bubble and Momen is a trade-off between a high-risk, high-cost metered model and a low-risk, low-cost predictable model. The composition of the total cost is revealing. For Bubble, across all high-load archetypes, the expense is overwhelmingly dominated by the variable, and potentially volatile, cost of WU overages. For the Social Network, over 99.8% of the estimated $311,303 monthly cost comes from WU consumption. This structure embodies high risk; any unforeseen increase in user activity could cause costs to spiral rapidly, a fear validated by user reports.2

In contrast, Momen's cost structure offers far greater certainty and affordability. Its use of hard RPS limits on shared plans acts as a trigger. For low-to-medium traffic apps, the cost is predictable based on add-ons. For high-traffic apps, the RPS limit forces an upgrade to the Single Tenant Kit, a $120/month plan with unlimited compute.3 This completely removes cost volatility related to usage spikes. For the Social Network and Job Board archetypes, this results in a fixed cost that is over 99.9% lower than Bubble's estimated variable cost. The risk of a surprise bill is eliminated.

Identifying Cost-Effectiveness Tipping Points

A platform's cost-effectiveness is highly dependent on an application's "resource signature." The updated analysis shows that Momen's model is more cost-effective across all analyzed signatures, with a critical tipping point defined by its RPS limits.

First, applications with low-to-moderate peak traffic (below 25 RPS) and low backend automation needs, such as the Internal Tool, can operate on Momen's shared plans. In these cases, Momen is significantly cheaper because its billable compute is minimal.

Second, for applications with high backend automation costs, regardless of their peak traffic, the Single Tenant Kit becomes the most strategic and cost-effective choice. Archetypes like B2B SaaS, Fintech, EdTech, and Healthcare fall into this category. By paying a flat $120 monthly fee, all variable compute costs are eliminated, providing ultimate predictability and a massive cost advantage over Bubble's metered model.3

Third, applications with high peak traffic (above 25 RPS), such as the Social Network, E-commerce Marketplace, and Job Board, are required to use the Single Tenant Kit. This plan's flat-rate pricing for unlimited compute makes it profoundly more cost-effective than Bubble's model, where costs scale linearly with the massive operational load. The RPS limit, therefore, is not just a technical constraint but a gateway to a highly predictable and affordable scaling path.

This leads to a clear decision-making matrix:

• If an application has low traffic and low backend automation needs, Momen's shared plans are the most cost-effective.

• If an application has high backend automation costs OR high peak traffic, Momen's Single Tenant Kit is overwhelmingly more cost-effective due to its fixed-price, unlimited-compute model.

• There are no modeled archetypes where Bubble is the more economical choice.

Final Recommendations for the No-Code Decision-Maker

Based on this comprehensive analysis, the following recommendations are offered to guide founders, product managers, and developers in their platform selection process.

Recommendation 1: Profile Your Application's Resource Signature First. Before committing to a platform, use the framework presented in this report as a template. Create a simple model of your application's expected usage, focusing on database size, object storage volume, and, most critically, computational load. For Momen, the key metric to forecast is Peak Requests Per Second (RPS), as this will determine whether you can use a shared plan or require the Single Tenant Kit.

Recommendation 2: Evaluate Your Business's Financial Risk Tolerance. The choice between Bubble and Momen is a strategic choice about risk. If your business operates on a fixed budget, requires predictable monthly expenses, or cannot tolerate the risk of a sudden, tenfold increase in your bill, favor Momen's predictable model. Given the cost disparity found in this analysis, Momen is the recommended choice for nearly any business profile where cost-efficiency is a factor. Bubble should only be considered if there is a specific, non-negotiable feature that Momen lacks and the business can absorb the significantly higher and more volatile costs.

Recommendation 3: Account for Hidden Cost Floors from Feature Requirements. Do not select a subscription plan based on your estimated resource consumption alone. First, identify the mandatory security (e.g., 2FA, SSO) and performance (Peak RPS) requirements for your application. Then, select the lowest-tier plan on each platform that provides these non-negotiable features, as detailed in Section 2.3. This will establish the true minimum monthly cost for your application.

Recommendation 4: Plan for Active Cost Management and Optimization. Regardless of the platform chosen, cost management is not a one-time setup. If you choose Bubble, you must budget significant engineering time for continuous performance monitoring and WU optimization to mitigate extreme costs.8 If you choose Momen, regularly monitor your Peak RPS to anticipate when you will need to upgrade from a shared plan to the Single Tenant Kit to ensure smooth performance as you scale.

Ultimately, the "right" no-code platform is the one that best aligns not only with an application's technical requirements but also with the business's overarching financial strategy. Based on this analysis, Momen's pricing model offers a compelling combination of predictability and cost-efficiency that makes it the superior financial choice for a wide spectrum of application archetypes.

Works cited

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