How a Global Enterprise Saved $1.2M a Year Moving Its Intelligence Layer from Databricks to Corvic

The company runs its business on six on-premises PostgreSQL production databases covering ERP, order management, CRM, customer service, supply chain and finance. Together they hold about 1 TB across roughly 2,800 tables: about 3 billion rows, with around 600 million in the largest order and shipment tables, and about 10 million row changes a day.

To analyze that data, the company had built an intelligence layer on Databricks. Nightly batch jobs exported Postgres tables, copied them into cloud storage and rebuilt Delta tables before a long chain of notebooks produced reporting tables. All in, the setup cost about $1.3M a year: roughly $500K in Databricks compute and cloud infrastructure for the nightly reloads and always-on SQL warehouses behind reporting, $250K in replication and ETL tooling, and about $550K for the three data engineers who spent most of their time keeping the pipelines running.

Even at that price, the data was a day old when it arrived. A failed nightly job meant sales and marketing worked from two-day-old numbers. Those teams still exported data into spreadsheets every week to build the pipeline, bookings and campaign reports leadership actually used.

Corvic replaced the export-and-rebuild cycle with a live intelligence layer that reads directly from the Postgres databases. The company's private network was connected to a dedicated Corvic tenant over a private VPC link, so production data never crossed the public internet and no database was exposed outside the company's network.

Change data capture reads the Postgres write-ahead log (WAL) through logical replication and streams every insert, update and delete into Corvic, so new orders, quote changes and shipments land in Corvic as they happen instead of in a nightly batch. Corvic models the data around how the business actually works, with customers, accounts, opportunities, quotes, orders, products, shipments and campaigns linked by their real relationships, so questions that used to need hand-written joins across six databases become a single query.

On top of that layer, the company built live dashboards for its sales and marketing teams in Corvic, covering pipeline and bookings by region, quote-to-order conversion, campaign-sourced revenue and backlog by product line. They update every hour from the latest Postgres data, and anyone can ask follow-up questions of the same data in plain language.

The whole rollout took less than a week: private connectivity on day one, CDC running across all six databases by day three, and the first live dashboards in front of the sales team by day five.

1. 1Connect privatelyThe company's network is linked to a dedicated Corvic tenant over a private VPC connection. No public endpoints and no database exposed outside the company's network.
2. 2Stream changes with CDCChange data capture reads the Postgres write-ahead log through logical replication and streams every insert, update and delete into Corvic, with no nightly exports and no load on production queries.
3. 3Model the businessTables from six databases are linked into the entities the business uses: customers, opportunities, quotes, orders, products, shipments and campaigns.
4. 4Serve live dashboardsSales and marketing dashboards are built on that model and update every hour, so no number is more than an hour old.
5. 5Ask follow-up questionsTeams can ask questions of the same live data in plain language and get answers that show where each number came from.

The intelligence layer now costs $120K a year, down from about $1.3M on Databricks. That saves about $1.2M every year and more than $3.5M over three years. Most of the savings came from no longer copying every table and recomputing every report each night, retiring the separate replication tooling, and freeing the three engineers who maintained the batch pipelines to work on new projects.

Sales and marketing no longer build their weekly reports by hand. The live dashboards replaced the spreadsheet exports and save the teams about 30 hours a week. Because the numbers update every hour instead of once a day, the teams now act on today's pipeline instead of yesterday's.

You don't need a lakehouse rebuild to get live answers from your operational data. In Corvic, a data team can:

1. 1Connect your network privatelyLink your VPC or data center to a dedicated Corvic tenant so production data stays on private networks.
2. 2Turn on CDCPoint Corvic at your Postgres or other production databases and stream changes as they happen instead of exporting them every night.
3. 3Describe your businessTell Corvic which entities and relationships matter and it links tables across databases into one model you can query.
4. 4Build the dashboards your teams ask forDescribe the views sales, marketing or operations need and choose how often they update, hourly or faster.