Recently, Fivetran changed its pricing strategy from account-based MAR (Monthly Active Row) discounts to connector-level discounts. For eCommerce companies that depend on a holistic view of their operations by pulling data from multiple platforms, this new pricing structure from Fivetran introduces a layer of financial unpredictability that can be particularly challenging to manage.
In this post, we’ll break down how Fivetran’s MAR model tends to get pricey fast. We will also show you how alternatives like Saras Daton offer a more predictable and affordable way to integrate data. If you're reevaluating Fivetran or just exploring better options, this guide is for you.
Why Fivetran's new pricing hurts eCommerce businesses
Fivetran’s MAR-based pricing model doesn’t align well with the operational and data needs of eCommerce brands. Here are some reasons why:
1. eCommerce relies heavily on real-time data
eCommerce teams track customer behavior in real time: clicks, cart events, purchases, returns, and more. These are high-frequency, event-driven data streams, i.e. exactly the kind that balloon MAR counts under Fivetran. Every click, every cart update, every order change is another MAR. The cost of capturing real-time signals becomes unjustifiable, especially during peak traffic periods like sales or product drops.
Let’s say you track clickstream data to personalize recommendations. If 50,000 users each trigger just 10 events per day, that adds up to 15 million MARs a month — before a single order is even placed. With Fivetran, that translates into massive, unpredictable costs just to access the data you need for customer experience optimization.
2. Nested data is common and penalized
eCommerce platforms like Shopify, TikTok Shop, or Amazon Marketplace often return nested or semi-structured data (e.g., line items inside orders, product attributes inside SKUs).
Fivetran normalizes all of it into multiple flat rows, which massively increases your MARs. So, for eCommerce companies syncing thousands of orders per day, this can easily lead to 10x or more inflated row counts, making routine data syncs disproportionately expensive.
After Fivetran’s normalization, 1 order could turn into 20+ rows. If you sync 100,000 orders per month, you could be billed for 2+ million MARs, despite only having 100K source records. This happens purely due to how the data is structured.
3. Frequent updates are a given in eCommerce
Inventory levels, pricing, promotions, customer profiles — these change constantly in an eCommerce setting. With Fivetran, any change, no matter how small, re-triggers the MAR. That means even a price change on a product or a restock can lead to thousands of additional MARs. You’re charged not based on value, but on volume. That’s a mismatch for businesses with dynamic catalogues and high SKU turnover.
Say your catalog has 15,000 SKUs, and each product updates price or stock twice a day. That’s 30,000 MARs daily, even if nothing else changes. Once you add customer profile updates, loyalty program tracking, and returns, you’re suddenly paying for millions of row updates that aren’t adding net new business insight.
4. High-volume sales means high-volume costs
Success in eCommerce should drive scale, but Fivetran’s pricing punishes it. If your brand grows and you're processing more transactions or customer touchpoints, your costs rise linearly or even exponentially. This makes scaling with Fivetran feel like walking a tightrope: every new channel you connect (e.g., Amazon, TikTok, Meta Ads) means one more MAR pipeline to manage without any cross-connector savings anymore.
5. Data costs become hard to forecast
Marketing and operations teams rely on clear, predictable budgets. But with MAR pricing, costs depend on unpredictable factors: how much data is updated, how often people interact with the brand, how complex your schema is. One busy sale week or product catalog change can spike costs. This unpredictability is especially hard for eCommerce brands where seasonality, campaigns, and launches drive huge but temporary activity bursts.
Let’s say you launch a Black Friday campaign and traffic surges. Suddenly, your site tracks 10x more product views, thousands of flash sale orders, and heavy inventory adjustments. This activity drives a spike in MARs, even if your revenue-per-order remains flat. At the end of the month, finance gets hit with a $10K+ bill, which is double the previous month without any early warning. It’s a budgeting nightmare.
6. Initial loads are painful for historical analysis
eCommerce brands often want historical data to train models, segment customers, or evaluate performance over time. But with Fivetran, syncing that historical backlog of orders, customers, and events immediately racks up MARs, making the initial setup financially painful. This deters teams from building long-term intelligence or consolidating across older platforms — even though that’s critical for growth and retention.
Imagine a brand migrating to a modern data stack. They want to sync 2 years of historical sales and customer data from Shopify. That’s 1.2 million orders, each with nested line items and fulfillment history. After normalization, the first sync could exceed 15 million MARs, resulting in a first-month bill of $15K or more, just to get the historical foundation in place. Many brands skip this entirely, losing out on historical analysis.
What should you look for instead?
At Saras Analytics, we understand the unique data challenges of eCommerce. That’s why we’ve built Daton not as a clone of Fivetran, but as an intentional, focused response to the gaps that generic ELT tools leave behind, especially for online retailers and D2C brands. Daton was designed to be more predictable in cost, more meaningful in output, and more aligned with the actual day-to-day needs of eCommerce operators and analysts.
Comparison: Why Daton is a better option for eCommerce
Here are some reasons that show why Daton is built to serve eCommerce needs more predictably and affordably.
1. Connector ecosystem
Fivetran: Here, you do get a very extensive library of 700+ connectors. But they cover a broad range of sources across various industries. It has a limited number of eCommerce-related connectors (e.g., Shopify, Amazon), and custom connector development can be costly and may involve exclusivity periods.
Daton: On the other hand, you get a more focused library of 200+ connectors specifically made for eCommerce and marketing platforms. It offers a No-Code Connector Development Kit (CDK) for users to build custom connectors without coding. New connectors built via the CDK become available to all customers at no extra charge.
It boasts more dedicated connectors for specific platforms like Amazon, Shopify, Walmart, and even TikTok.
2. Pricing model
Fivetran: They employ a usage-based pricing model primarily based on Monthly Active Rows (MAR), which counts unique rows added or modified each month. This can lead to unpredictable and potentially high costs, especially for businesses with high data volume, frequent updates, and normalized data. The recent price update shifts to connector-level discounts, potentially increasing costs for multi-connector setups. Historical loads and premium connectors may incur additional fees.
Daton: Typically uses a subscription-based pricing model with predictable tiers, often based on business size or data needs, rather than MAR. This offers more cost predictability for eCommerce businesses. Overage costs and historical loads are often structured differently and can be more cost-effective. All connectors are usually included in the subscription price.
3. Specialization in eCommerce
Fivetran: Is a general-purpose ELT tool and does not offer out-of-the-box eCommerce-specific analytics models, industry KPIs, or pre-integrated dashboards. Users need to build their own analytics layer.
Daton: Is purpose-built for eCommerce. It offers pre-built eCommerce data models and Saras Pulse, a suite of ready-to-use dashboards and analytics tailored to retail needs. Daton pre-maps source data to commerce schemas, simplifying analysis.
4. Flexibility and customization
Fivetran: Known for its automation and managed service, which provides ease of use but can limit flexibility and customization of data extraction and loading processes. Custom connectors are available but require coding and may have cost implications.
Daton: Offers more adaptability and willingness to customize to meet customer needs. Their ability to build custom connectors quickly and potentially for free provides greater flexibility for unique data sources. Daton can also accommodate custom business logic and transformations.
5. Support and service
Fivetran: Provides broad, standardized support through documentation and a support portal. As a large-scale solution catering to multiple industries, support may feel generalized and responsiveness can vary. Moreover, Fivetran's primary focus is on enterprise clients such as JetBlue, Cisco, and Lufthansa Group—often leaving small to mid-sized businesses feeling like a lower priority.
Daton: Offers specialized, high-touch support tailored for eCommerce and D2C brands. This includes live chat, onboarding assistance, and a dedicated account manager. The team comprises eCommerce data experts who can advise on strategy and best practices.
Most notably, Daton integrates deeply with leading subscription platforms like Recharge, Skio, Ordergroove, and Stay, further demonstrating its commitment to the unique needs of eCommerce businesses.
To sum it up
Fivetran’s reputation as a market leader is well-earned. But for eCommerce brands, its recent pricing changes and generic platform approach have made it a harder choice to defend.
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Daton offers a compelling alternative, a platform that’s purpose-built for your business, priced for your growth, and designed to deliver value.
If you're tired of unpredictable bills, limited flexibility, and platforms that don’t understand your world, it’s time to make the switch.
Let’s talk. We’d be happy to show you how Daton can help your eCommerce business operate smarter and scale faster, without breaking the bank.
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