6 Real-World ETL Use Cases with Estuary Flow
After working in data for over a decade, one thing that remains the same is the need to create data pipelines. Whether you call them ETLs/ELTs or something else, companies need to move and process data for analytics.
The question becomes how companies are actually building their data pipelines.
What ETL tools are they actually using?
There are so many ETL solutions and options that it can be difficult to pick. Especially when there are dozens of articles touting the 12 best ETL tools.
So instead of just hyping up a bunch of tools, this article will focus on actual use cases surrounding a single tool.
Let’s dive into six ETL use cases for Estuary Flow, an ETL tool being used for everything from streaming to batch data pipelines.
If you’d like to read more about Estuary itself, you can find it in this article here, as this article will specifically be diving into use cases.
Six ETL Uses For Estuary Flow
Many companies need to extract data from sources like NetSuite, HubSpot, Salesforce, databases, etc and load them into their data warehouse. But there are so many tools that it can be difficult to select which is why we will be highlighting Estuary below.
Resend Replaces Fragile Pipelines with Real-Time Streaming for Analytics and Fraud Detection
As Resend’s customer base grew, so did the complexity of its internal data needs. The developer-focused email platform needed reliable insights into user behavior, not just for product analytics but also for fraud detection and operational decision-making.
Their prior setup relied on Fivetran as their ELT solution. However, they needed to find an alternative to Fivetran. Their current pipelines were breaking every couple of weeks and disrupting access to analytics.
That changed when they implemented Estuary Flow.
Their team replaced reactive data firefighting with real-time visibility, giving them fast, consistent access to the metrics they needed without burdening their production database.
The result? Better decisions, faster iteration, and stronger fraud detection, all on a more durable and cost-effective foundation. As Jonni Lundy, Resend’s COO, put it:
“Estuary Flow transformed how we operationalize our data for fraud, security, support, and beyond.. Instead of unreliable, expensive backfills, we have real-time visibility into platform activity. The proactive support and hands-on approach make all the difference.”
Headset Cuts Snowflake Costs by 40% After Replacing Airbyte with Estuary
For Headset, a leading provider of cannabis market intelligence, data is core to the business. They rely on fast, reliable ingestion from SQL databases into Snowflake to power real-time analytics for retailers, brands, and investors. But their previous setup, first with Fivetran, then Airbyte was anything but efficient.
While Fivetran delivered a solid performance, its pricing changes made it unsustainable. The switch to Airbyte saved money upfront but quickly introduced new problems: unreliable syncs, frequent outages, and massive Snowflake compute bills. Latency spiked without explanation, records went missing, and support was slow to respond, sometimes taking over a week to resolve critical issues.
That’s when Headset turned to Estuary.
With Estuary Flow, they replaced batch-heavy, failure-prone jobs with efficient streaming pipelines. The result? Near-instant ingestion, full data integrity, and a 40% drop in Snowflake compute costs. Estuary’s Snowflake integration alone used 75% fewer credits per load compared to Airbyte, and the difference was felt immediately.
Job runtimes shrank from hours to near real-time. Outages disappeared. And for the first time in months, the data team could trust their pipelines.
“Estuary has been a game-changer for Headset’s data infrastructure. Compared to our previous solutions, it has dramatically improved reliability while reducing our overall costs significantly. The real-time ingestion capabilities ensure that our analytics are always powered by the freshest, most accurate data without the operational headaches we faced before.”
Estuary didn’t just save money. It helped Headset reclaim confidence in its analytics stack.
Real-Time NetSuite Reporting Transforms Financial Planning for Leading Nutraceutical Brand
A top nutraceutical company in Australia was facing major friction in its financial reporting process. Monthly sales-to-COGS calculations were inconsistent, delayed, and often riddled with errors due to fulfillment-based processing in NetSuite. The finance team lacked timely, reliable visibility into gross profit at the banner and store level hindering planning and performance tracking.
Earlier attempts to customize NetSuite fell short. Manual reporting was still the norm, and the company struggled to analyze financial performance across customers, products, and categories with confidence.
That changed when Fornax found Estuary.
Fornax designed the KPI framework and reporting automation strategy, while Estuary implemented real-time ELT pipelines that seamlessly streamed data from NetSuite and other third-party systems. Together, the teams eliminated manual processes and enabled real-time financial analytics at both product and customer-segment levels.
This allowed the company to reduce hours upon hours of manual work and gain far more confidence in their data and reporting.
Recart Delivers Real-Time Segmentation and Analytics with Estuary Flow + SingleStore
Recart, a marketing automation platform built for Shopify stores, powers over 500 million monthly events. At the heart of its product is a segmentation engine that must react instantly to customer behaviors, whether it’s sending an SMS after checkout or triggering performance reports for internal teams.
But their existing setup MongoDB plus webhook-based pipelines couldn’t keep up. High latency, unreliable syncs, and no support for real-time integrations with tools like Stripe or HubSpot led to bottlenecks across segmentation, analytics, and internal reporting.
To modernize their stack, Recart turned to Estuary Flow and SingleStore.
Estuary’s real-time Change Data Capture (CDC) pipelines continuously sync updates from MongoDB into SingleStore, delivering sub-second latency and ensuring segmentation logic always runs on fresh data. Meanwhile, SingleStore provides the high-speed SQL engine needed to support instant analytics across billions of records without burdening production systems or requiring a dedicated data engineering team.
The payoff was, real-time segmentation with sub-second event ingestion, live campaign dashboards for customers and internal teams, lower infrastructure costs, and more!
“Estuary became our real-time data backbone without the cost or complexity of traditional solutions. We replaced a fragile, high-maintenance pipeline with a managed system that just works and scales.”
With Estuary and SingleStore, Recart built a modern data platform that supports both operational growth and customer experience, proving you don’t need a massive team to run a high-performance, real-time analytics engine.
David Energy Prioritizes Reliability with Estuary Flow
David Energy is on a mission to run the grid 24/7/365 on clean, renewable energy, a task that demands real-time insight into power generation, consumption, and market conditions. The company monitors high-frequency data from smart meters, electric vehicles, and energy markets to optimize grid performance. But powering clean energy shouldn’t require constantly fixing broken data pipelines.
Unfortunately, that’s what David Energy faced when trying to move PostgreSQL data into Snowflake. Fivetran was stable but prohibitively expensive, costing 8x more than the rest of their infrastructure combined. Airbyte was free, but was inconsistent and frequently broke. Neither option could offer the reliability and efficiency needed to support mission-critical analytics.
Estuary Flow changed that.
With Estuary’s streaming-first architecture and CDC-powered replication, David Energy finally found a solution that was both technically sound and cost-effective. Their PostgreSQL to Snowflake pipeline became a low-latency, exactly-once, reliable stream with no resyncs or manual patchwork needed.
“It was just a better technical approach,” said Sam Strasser, CTO of David Energy. “Estuary’s architecture fits our use case perfectly low latency, high reliability, and strong support without the price tag.”
David Energy no longer had to babysit pipelines and gained responsive support without extra costs.
For a company dedicated to reliability at the grid level, Estuary provided the same peace of mind in their data infrastructure, letting the team focus on keeping the lights (and the wind turbines) on.
Livble Achieves Real-Time Operational Excellence and 50% Lower Costs with Estuary Flow
As a fintech company redefining how renters pay their rent, Livble depends on real-time data to drive everything from underwriting to credit modeling to customer communications. With data powering critical decisions, delays or failures aren’t just inconvenient—they’re costly.
But Livble’s previous ETL tools couldn’t keep up. Syncs were too slow, failures were too frequent, and batch-based architectures couldn’t deliver the continuous data flow needed for modern machine learning, financial reporting, or tenant engagement. The team needed a platform that could scale with their ambition, and fast.
That’s when they found Estuary Flow.
By streaming change data from MySQL to Snowflake in near real time, Estuary enabled Livble to unlock faster decision-making and tighter feedback loops across the business. Dashboards in Retool and Superset now reflect the latest data. Credit models update as new property and Plaid data flow in. Customer notifications are powered by timely insights, not stale reports.
The impact was immediate, with a 30% reduction in platform costs and a 50% lower Snowflake spend, thanks to delta-aware streaming and, of course, reliable, real-time syncs that replaced fragile ETL jobs.
“We needed something self-serve, fast, and reliable, and Estuary delivered exactly that. It’s a huge unlock for our operations, reporting, and machine learning,” said Uri Vinetz, Director of Data at Livble.
For a lean team supporting a high-volume, high-stakes platform, Estuary Flow didn’t just make the data stack more efficient, it made the business more agile.
Final Thoughts
Whether you’re looking to set-up an ETL pipeline or you’re looking for an alternative to Fivetran, Estuary has been helping dozens of companies reliably build data pipelines. Above are just a few examples of use cases they’ve shared over the past few years.
Personally, I’ve been using Estuary for many of my clients, even before I became an advisor to them. They’ve helped me keep costs low and focus on impact.
As always, thanks for reading!
Also! Don’t forget to check the articles below.
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