10 Tips for Negotiating Your SnowFlake Agreement
Snowflake is a powerhouse for modern data management, giving businesses real-time scalability and lightning-fast analytics.
Its unique architecture separates storage and compute, slashing costs while boosting performance.
In 2024, Snowflake reported $2.8 billion in revenue, a 33% jump from the previous year. With over 10,600 customers, including many Fortune 500 companies, it’s a go-to solution for large-scale operations.
But negotiating a Snowflake agreement isn’t straightforward.
This guide is a deep dive into some key steps and a calculated approach to securing favorable terms while avoiding unnecessary costs.
Why is Snowflake Negotiation Important?
Negotiating a Snowflake contract, as with all enterprise software contracts, is about securing favorable terms that optimize your data usage while controlling costs.
Unlike standard agreements, Snowflake operates on a consumption pricing model, meaning your total cost depends on how much storage and compute power you use.
Without a well-negotiated software agreement, you risk overpaying for unnecessary resources, losing flexibility in contract terms, and missing out on strategic performance incentives.
Snowflake’s enterprise license agreements require a nuanced approach to ensure alignment with your organization’s compensation philosophy and long-term data strategy.
Here’s why negotiation matters:
Cost Optimization – Snowflake’s fully-loaded costs vary based on storage, compute, and additional costs like data egress fees. A strong negotiation strategy helps control these expenses
Flexible Contract Terms – Enterprise software agreements should include ideal software contract terms that allow for scaling, usage adjustments, and renegotiation based on critical business needs
Performance Incentives – Negotiating compensation components such as discounts, credits, and reserved capacity pricing ensures a beneficial arrangement that maximizes Snowflake’s value
Avoiding Hidden Costs – Poorly structured agreements can introduce potential costs tied to data replication, cloud provider charges, and long-term commitments that don’t fit your consumption-based models
Strategic Growth Alignment – A well-negotiated Snowflake contract helps make sure your software license terms align with your company’s data strategy, preventing unnecessary delays in scaling analytics capabilities
10 Tips for Negotiating Your Snowflake Agreement
1. Optimize Compute Warehouse Scaling to Avoid Overages
Snowflake's consumption-based pricing model (shown below) charges customers based on their actual usage of compute resources and data storage. This approach offers flexibility and allows organizations to scale resources up or down according to their needs.
To optimize costs, it's essential to analyze your organization's historical usage patterns. For example, virtual warehouse compute costs typically account for 80% of a Snowflake customer's bill. By understanding past consumption trends, you can make informed decisions about whether to opt for on-demand pricing or to negotiate reserved capacity pricing, which may offer discounts for committing to a certain level of usage over time.
However, overcommitting to compute credits without accurate forecasting can lead to unnecessary expenses. This means you’ll need to conduct a thorough analysis of your workload requirements before entering into any reserved capacity agreements.
2. Secure Enterprise-Grade Features Without Unnecessary Add-Ons
When negotiating Snowflake's enterprise license agreements, it's important to assess which features align with your organization's needs to avoid unnecessary costs. Snowflake offers advanced functionalities such as data sharing, Snowpark, and zero-copy cloning, each designed to improve data management and analytics. However, incorporating features that don't serve your specific use cases can lead to inflated expenses without corresponding benefits.
Data Sharing allows seamless sharing of live data across different accounts without the need for data duplication. This feature is particularly useful for organizations that require real-time data collaboration with partners or clients. If your business operations don't involve such collaborations, opting out of this feature can be a good way to save costs.
Snowpark provides a developer framework for building data applications using familiar programming languages like Java and Scala. While Snowpark offers powerful capabilities for data engineering and machine learning tasks, you should consider whether your team uses these specific languages and requires this functionality. If not, excluding Snowpark from your agreement can prevent unnecessary expenditures.
Zero-Copy Cloning allows for instantaneous cloning of databases, schemas, or tables without additional storage costs, as no physical data is duplicated. This feature is invaluable for testing and development environments where quick replication of data structures is necessary. However, if your workflows don't involve frequent cloning operations, this feature might not be essential. According to Secoda, zero-copy cloning offers significant benefits for data management, development, and testing environments.
By critically evaluating your organization's requirements and aligning them with Snowflake's feature offerings, you can negotiate a bespoke agreement that maximizes value and minimizes unnecessary costs.
3. Cap Data Egress and Replication Costs Across Cloud Regions
In Snowflake, data egress refers to the transfer of data out of your Snowflake environment, either to a different region within the same cloud platform or to an entirely different cloud provider. Such transfers incur per-byte fees, shown below, which can accumulate rapidly if not properly managed. Notably, while Snowflake does not charge for data ingress (importing data into Snowflake), data egress (exporting data) does incur costs.
Replication, a feature that allows databases and other account objects to be copied across multiple accounts or regions, also contributes to data transfer expenses. These costs are twofold: data transfer fees for moving data between regions and compute resource costs associated with the replication process. For instance, replicating a 1 TB database from one region to another can result in substantial data transfer charges, depending on the specific regions and cloud providers involved.
To mitigate these expenses, you should negotiate contract terms that cap potential costs related to inter-region data movement. This includes setting predictable billing structures and understanding the specific scenarios that trigger data transfer fees. This way, organizations can effectively manage their Snowflake expenditures and avoid unforeseen charges.
4. Negotiate Long-Term Reserved Capacity Pricing for Workloads
For organizations with consistent and predictable workloads, Snowflake's pre-purchased capacity model offers an opportunity to optimize costs through reserved capacity pricing. This approach allows you to commit to a specific amount of Snowflake credits in advance, often at discounted rates compared to on-demand pricing.
By aligning your contract terms with your organization's workload requirements, you can secure a beneficial arrangement that ensures cost predictability and potential savings. This calculator can help you work out your Snowflake costs based on predicted usage.
When negotiating reserved capacity agreements, consider workload-specific performance incentives. For example, if your organization runs stable, continuous data processing tasks, you might benefit from performance improvements that Snowflake has implemented. According to Snowflake, query durations for customers' stable workloads improved by 40% between August 25, 2022, and October 31, 2024, as the graphic below shows. Taking advantage of such enhancements can lead to more efficient compute usage and maximize the value of your reserved capacity.
It's also important to monitor and adjust your reserved capacity commitments over time. As your organization's data needs evolve, regularly reviewing your capacity usage ensures that your reserved credits align with actual credit consumption patterns. This proactive approach helps prevent over-commitment or under-utilization, so that your investment in Snowflake's services remains cost-effective and aligned with your operational requirements.
5. Align Your Licensing Model with Query Performance Needs
Aligning your Snowflake licensing model with your organization's query performance needs is crucial for cost-effective and efficient data operations. Snowflake's architecture offers features like multi-cluster warehouses and concurrency scaling to manage varying query loads, but you need to understand their implications on both performance and cost.
Multi-cluster warehouses in Snowflake allow for automatic scaling to handle fluctuations in query concurrency. When the demand for queries increases, Snowflake can automatically start additional clusters to maintain performance, and as the load decreases, it shuts down these clusters to conserve resources. The image below shows a visualization of this process.
This dynamic scaling ensures that query performance remains consistent without manual intervention. However, it's important to note that each active cluster consumes compute credits, and without proper configuration, costs can escalate unexpectedly.
To manage costs effectively, Snowflake provides a SCALING_POLICY parameter that determines how clusters are added or removed. By setting this policy appropriately, you can control the scaling behavior to align with your workload patterns, which ensures that resources are used efficiently without running up unnecessary expenses. For example, starting with a smaller number of clusters and gradually increasing based on observed demand can help find the optimal balance between performance and cost.
Additionally, Snowflake's concurrency scaling feature automatically adds transient clusters to handle sudden spikes in concurrent queries to drive consistent performance. While this feature improves user experience during peak times, you still need to monitor its usage, as it can lead to additional charges if not managed properly. Understanding the conditions under which concurrency scaling is triggered and configuring thresholds accordingly can help you maintain predictable billing.
By carefully configuring these features and negotiating terms that reflect your organization's specific query performance requirements, you can negotiate a licensing model that provides both high performance and cost efficiency. Regularly reviewing and adjusting these settings in response to changing workloads will further ensure that your Snowflake environment remains aligned with your business goals.
6. Push for Discounts on Near-Zero Compute Features Like Snowpipe
Snowpipe is Snowflake's continuous data ingestion service, and it allows the automated loading of data as it arrives in cloud storage. The image below shows the Snowpipe process.
This serverless feature eliminates the need for manual data-loading processes by offering a seamless and efficient method for real-time data integration. However, it's essential to understand the associated costs to manage your budget effectively.
Cost Structure of Snowpipe:
Compute Costs: Snowpipe operates on a serverless compute model, meaning Snowflake manages the necessary resources. The compute costs for Snowpipe are 1.25 times that of standard virtual warehouses. For example, if an X-Small warehouse costs 1 credit per hour, Snowpipe would cost 1.25 credits for equivalent usage.
Per-File Overhead: In addition to compute costs, Snowpipe imposes a charge of 0.06 credits per 1,000 files processed. This fee accounts for the overhead associated with managing each file ingestion event.
Strategies for Cost Optimization:
Batch Small Files: If your workflow involves numerous small files, consider batching them before ingestion. This approach reduces the per-file overhead charges, leading to more efficient use of credits.
Negotiate Contract Terms: For organizations with high-frequency data ingestion needs, negotiate contract terms that provide discounts or caps on Snowpipe-related charges. By aligning your agreement with your ingestion patterns, you can achieve more predictable and manageable expenses.
By implementing these strategies and maintaining awareness of Snowpipe's cost structure, you can effectively manage and optimize your data ingestion expenses within Snowflake.
7. Structure Compute Credit Allocation Based on Workload Type
Effectively managing compute credit allocation in Snowflake helps you optimize performance and control costs. Snowflake's flexible architecture allows organizations to tailor compute resources to specific workload requirements, which ensures efficient operations across diverse data processing tasks.
Snowflake's compute resources are primarily managed through virtual warehouses, which are clusters of compute resources that execute queries, load data, and perform other data manipulation tasks. Each virtual warehouse operates independently, allowing for workload isolation and tailored performance tuning.
For example, a virtual warehouse dedicated to ETL (Extract, Transform, Load) processes can be sized and scheduled differently from one handling ad-hoc analytical queries, aligning resource allocation with workload demands.
To further improve cost management, Snowflake offers features like auto-suspend and auto-resume, which automatically suspend warehouses during periods of inactivity and resume them when new queries are initiated. Configuring these settings appropriately ensures that compute credits are utilized only when necessary, reducing wastage. For instance, setting a short auto-suspend interval for warehouses with sporadic usage patterns can lead to significant cost savings without compromising performance.
The image below shows an example of how Snowflake usage is charged:
Working with procurement experts to design a compute credit allocation strategy that aligns with your organization's workload types is an excellent strategy. This involves analyzing usage patterns, forecasting demand, and negotiating contract terms that give you flexibility in credit distribution. By doing so, organizations can make sure that compute resources are allocated efficiently and able to support large-scale operations without unnecessary delays or costs.
8. Negotiate Favorable Terms for Unused Credits and Rollover Options
Effectively managing unused Snowflake credits is a great way for organizations to optimize their data platform investments. Snowflake's policies allow for the rollover of unused credits into new annual contracts upon renewal, which offers a ton of flexibility. However, the specifics of these rollovers can vary based on contractual agreements, so it’s essential to negotiate terms that align with your organization's usage patterns.
To get the best arrangement, it's advisable to negotiate contract terms that permit the rollover of unused credits into subsequent periods. This approach gives you a safety net against unforeseen fluctuations in data usage and allows your organization to make full use of its investment without incurring additional costs. Additionally, exploring options to convert unused compute credits into storage credits or other services can lead to even more flexibility, so that resources are allocated where they're most needed.
Engaging with procurement experts during contract negotiations can result in win-win solutions that closely match your organization's specific needs. By proactively addressing the management of unused credits, you can secure favorable terms and a more cost-effective Snowflake deployment.
9. Benchmark Pricing Against Other Snowflake Customers in Your Industry
Benchmarking your Snowflake pricing against industry peers is a strategic approach to secure competitive rates and align with standard practices. Snowflake's pricing structure is influenced by various factors, including role level, industry, and deal size. Understanding how these elements impact costs can give you valuable leverage and lead to successful negotiations.
Role Level: Snowflake offers tiered pricing models designed to suit diverse customer needs. The pricing varies based on contract ranges, the product tier chosen, and the employee headcount. For example, virtual warehouses, which handle compute tasks, vary in cost based on size. An X-Small warehouse consumes 1 credit per hour, while a 6X-Large consumes 512 credits per hour. Choosing the appropriate warehouse size can significantly impact overall costs.
Industry: Different industries may have varying data storage and processing requirements, influencing Snowflake's pricing structures. For instance, industries dealing with large-scale data analytics might benefit from specific pricing models tailored to their needs. Engaging with procurement experts who have experience in your industry can provide insights into standard pricing and help negotiate terms that reflect typical usage patterns.
Deal Size: Larger contracts often come with more favorable pricing due to economies of scale. Snowflake's pricing is consumption-based, allowing customers to pay for only what they use. This approach offers flexibility and control, enabling customers to scale up or down to meet demand while gaining clear visibility into their usage and spend.
To effectively benchmark your pricing, consider collaborating with procurement experts who have access to industry-specific pricing data. This collaboration can provide valuable insights into standard pricing models and assist in negotiating terms that align with your organization's unique requirements.
By thoroughly understanding how role level, industry, and deal size influence Snowflake's pricing, you’ll be better placed to secure a contract that offers both value and flexibility.
10. Secure an Exit Strategy with Cost-Controlled Data Migration
When planning a transition away from Snowflake, it's important to anticipate and manage potential data export costs to avoid unexpected expenses. Snowflake charges per-byte fees for data egress, particularly when transferring data to different regions or external platforms. For instance, moving data out of Snowflake to another region or cloud provider incurs specific charges, which can accumulate significantly depending on the volume of data and the destination.
To mitigate these potential costs, it's best to negotiate software license terms that include provisions for capping exit-related expenses. These terms can encompass predetermined rates for data extraction or allowances for a certain volume of data transfer at no additional cost. By securing these terms upfront, your organization can be sure that data migration processes remain within budget constraints, even during transitions.
Additionally, you need to understand the specific scenarios that trigger data transfer fees. As we learned earlier, Snowflake does not charge for data ingress (importing data into Snowflake); however, data egress (exporting data) to different regions or external platforms does incur costs. Being aware of these distinctions allows for more accurate forecasting and budgeting during migration planning.
By proactively addressing these considerations in your contract negotiation process, you can establish a clear and cost-effective exit strategy and make sure that data migration efforts don’t lead to unforeseen financial burdens.
Common Mistakes When Negotiating Your Snowflake Contract
Negotiating a Snowflake contract requires more than just securing a discount.
Missteps in pricing models, workload forecasting, and licensing terms can lead to unnecessary costs and performance limitations.
To get the best deal, avoid these common pitfalls:
1. Overcommitting to Compute Credits Without a Usage Analysis
Snowflake offers discounts for pre-purchasing credits, but many businesses lock in too many without accurately forecasting usage.
How to avoid it: Analyze past workloads and negotiate flexibility in adjusting committed spend over time. Push for rollover terms that allow unused credits to be applied in future cycles.
2. Ignoring Data Egress and Cross-Cloud Replication Costs
Transferring data between Snowflake regions or cloud providers incurs fees, which can quickly add up in multi-cloud environments.
How to avoid it: Negotiate caps on data egress charges and secure committed-use discounts for inter-region replication. If you plan to scale globally, ensure cost predictability in data movement.
3. Paying for Unnecessary Features
Snowflake bundles services like Snowpark, data sharing, and zero-copy cloning into enterprise agreements, but not every company needs them all.
How to avoid it: Audit feature usage before signing a contract. Remove unnecessary add-ons or negotiate performance-based incentives that allow gradual adoption without upfront costs.
4. Failing to Define Concurrency Scaling Limits
Snowflake’s multi-cluster warehouses and concurrency scaling automatically add compute power during peak loads, but this can create unpredictable charges.
How to avoid it: Set clear scaling policies to limit the number of clusters Snowflake can provision. Request visibility into concurrency scaling charges to track overages in real-time.
5. Lacking an Exit Strategy for Data Migration
If you ever need to leave Snowflake, high data egress costs can make migration expensive. Many companies overlook this when signing long-term contracts.
How to avoid it: Secure ideal software contract terms that cap exit-related expenses, and negotiate free or discounted data export credits if migration is needed in the future.
What’s Next?
Negotiating your ServiceNow contract isn’t just about cutting costs—it’s about building flexibility into your agreement. Hidden fees, rigid licensing, and vague renewal terms can lock you into unnecessary expenses and limit your ability to scale. A well-structured contract means you only pay for what you actually use while keeping future growth in mind.
Before signing, ask yourself: does this contract give your business control, or does it put you at the mercy of fixed pricing and unpredictable costs? The right negotiation strategy can save millions and prevent operational headaches. ServiceNow rewards those who plan ahead — make sure you’re one of them. Need help gaining the upper hand? Contact us today and let’s craft a smarter ServiceNow strategy together.
