Track.coDatabricks

Track.co + Databricks

Track.co is a customer experience management platform that helps companies measure and improve customer satisfaction by providing detailed insights to enhance support and build customer loyalty. Databricks, in turn, is a serverless Big Data solution that delivers robust capabilities for large-scale data storage and analytics.

With Erathos, you can integrate Track.co data into Databricks in just a few minutes. Our platform handles the entire data movement process into your analytics environment and lets you join that data with other sources in your Data Warehouse. That means your time goes to what really drives value — extracting actionable insights and making more data-driven decisions.

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WePayments
Brick
CCM
Simplified extraction and ingestion

Move data in a few clicks

1

Connect your source

Authenticate your account and you're done. 100+ ready-made connectors, no code required.

2

Configure the sync

Pick the tables, the schedule and the update type: batch, cursor-based incremental or CDC.

3

Choose your destination

Load into BigQuery, Redshift, Databricks, PostgreSQL, ClickHouse, Amazon S3 and more.

Which Track.co data does Erathos sync with Databricks?

The integration automatically syncs the main Track.co objects:

  • Customer health (Health Score) — current score and historical changes
  • NPS — responses, detractors, passives, and promoters
  • Product usage — features used, frequency, and engagement
  • Churn risk — alerts, signals, and actions taken
  • Segments — customer segmentation classification and criteria
  • Interactions — meetings, QBRs, and CS contact history

Why sync Track.co with Databricks?

Track.co centralizes the customer health view, but in a silo. In Databricks, you combine health score, NPS, and product usage with financial and support data — identifying churn signals weeks in advance, calculating the true financial impact of retention, and building predictive models with all available data.

How it works

Erathos connects to Track.co via the official API and syncs your data incrementally — only new or updated records are processed on each run, keeping pipelines fast and Databricks costs predictable. You choose the sync frequency (from every 5 minutes to daily), which objects to sync, and the target dataset. Each run is fully observable: execution time, rows processed, errors with context, and instant alerts via Slack or email if anything goes wrong.

Why companies are moving data from Track.co to Databricks with Erathos

Centralizing Track.co data in Databricks has never been this simple.

Erathos is a data ingestion platform for Customer Success and data teams. With the Track.co connector, you automatically sync customer health, NPS, product usage, and churn data to Databricks—with full observability for every pipeline run and smart alerts.

Why do data teams choose Erathos for Track.co?

Data in your data warehouse in minutes

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Building data-driven stories

Every new source implementation, if I had to do it myself, would take about two or three months. With Erathos, it's done in a few hours. I don't need the skills of a data engineer to generate real value from the company's data.

Bruno Rosso
Bruno RossoData Analyst, Brick Software

Erathos revolutionized data management at WE. By integrating multiple SaaS tools into a single DW, our technical team now focuses on the core business. We implemented dashboards with insights across every area, enriching our organizational culture and improving our decision-making.

Matheus Nunes
Matheus NunesCTO & co-founder, WePayments

We used to have a lot of rework, and now we don't. It's more efficient to work this way. If it's not your core business, hire Erathos. Spend your time modeling your own domain, not someone else's.

Carlos Schwabe
Carlos SchwabeCo-Founder & CDO, Brick

If I didn't have this infrastructure, I'd need three or four people to do what Erathos does today. I was able to generate real value from my data with a much leaner setup than I thought I'd need. That's the core of building a data-driven culture: the team only uses data when they can trust it.

Thiago Paz
Thiago PazCFO, Brick

Erathos brought a practical turnaround at CCM. We were able to integrate financial systems, CRM, and processes with BigQuery in just a few clicks, with no technical team required. That gave us a reliable data warehouse that powers automations, dashboards, and even our customer service bots.

Gustavo Loforte
Gustavo LoforteTechnology Manager, CCM Group

The robustness and efficiency of Erathos's connectors — whether for Meta, Google, RD Station, or ERPs like Bling and Conta Azul — make the whole process much faster and more reliable. The technical documentation is extremely well put together and intuitive, which makes implementation much easier.

Sayuri Valente
Sayuri ValenteProject Manager, Xperiun
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FAQ

Frequently Asked Questions

Erathos is a data ingestion platform built for reliability, transparency, and control. We help data teams connect tools like Track.co to their data warehouse—with full observability into every run, zero maintenance, and none of the opacity of traditional market tools.

Erathos syncs Customer Health data, NPS, product usage, segments, churn risk, and interactions from Track.co to Databricks. Scores and engagement metrics are also exported automatically.

You can configure the sync frequency from every 5 minutes up to daily at the table level. Erathos uses incremental synchronization—only new or updated records are processed in each run, keeping the Track.co pipeline efficient and Databricks costs predictable.

Erathos automatically detects failures and sends alerts to your email, Slack, or Discord with full context—not just "job failed." Smart retries handle transient errors, and every execution is logged with run time, processed rows, and error context so your team can debug in minutes, not hours.

Yes. Every Erathos connector includes a 14-day free trial. Connect Track.co to Databricks and start syncing immediately—no credit card required.

Data ingestion with control, observability and scale