Freshchat + Databricks
Freshchat is a messaging and live chat platform designed to make communication between companies and customers easier. Databricks, in turn, is a serverless big data solution that provides robust capabilities for storing and analyzing data at scale.
With Erathos, you can integrate data from Freshchat into Databricks in just a few minutes. Our platform handles the entire data movement process into your analytics environment and lets you join this data with other sources in your data warehouse. That way, your time is spent on what truly creates value — uncovering actionable insights and making more data-driven decisions.
What Freshchat data does Erathos sync with Databricks?
The integration automatically syncs the main Freshchat objects:
Tickets — status, priority, assignee, and resolution time
Conversations — messages, replies, and conversation history
Agents — individual performance and support workload
SLAs — compliance, breaches, and metrics by category
CSAT — satisfaction ratings and customer comments
Tags and categories — contact-reason taxonomy
Why sync Freshchat with Databricks?
Freshchat data reveals what your customers need — but it lives separately from product, marketing, and finance data. In Databricks, you can correlate ticket volume with churn, calculate the true cost of support by segment, and identify which features generate the most support before they turn into critical issues.
How it works
Erathos connects to Freshchat 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), the objects to sync, and the destination dataset. Each run is logged with full observability: execution time, rows processed, errors with context, and instant alerts via Slack or email if anything goes wrong.
No credit card required.
Why do data teams choose Erathos for Freshchat?
Freshchat connector ready to use
Connect Freshchat to Databricks in minutes. Tickets, interactions, SLAs, and agent data are automatically synced—ready for analysis without manual processing.
Total control over your Freshchat pipelines
Configure frequency, sync type, and partitioning by table. Data arrives in Databricks ready for ML, analytics, and ad hoc queries—with predictable cost.
End-to-end observability
No more finding out about Freshchat failures when the business team complains. Every run is logged with execution time, processed rows, and error context. Automatic alerts via Slack, Discord, or email as soon as anything deviates from expected behavior — SLAs and satisfaction metrics always stay up to date.
Why companies move data from Freshchat to Databricks with Erathos
Centralizing Freshchat data in Databricks has never been easier
Erathos is a data ingestion platform for support and data teams. With the Freshchat connector, you can automatically centralize tickets, interactions, SLAs, and customer support data in Databricks—support data always available for analysis and dashboards.
Our Customers
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Simplified data ingestion
1
Select your data source
More than 80 plug-and-play connectors to consolidate data from multiple sources, eliminate time-consuming manual processes, and create a streamlined path forward.
2
Setup your pipeline
Manage your pipeline seemlessly. Select a sync hour, frequency and type at a table/endpoint level.
3
Select your data warehouse
Choose between Amazon S3, BigQuery, Databricks, Redshift and PosgreSQL to centrlize your data
FAQ
What is Erathos and how can it help my company?
Erathos is a data ingestion platform built for reliability, transparency, and control. We help data teams connect tools like Freshchat to their data warehouse—with full observability into every pipeline run, zero maintenance, and none of the black-box opacity of traditional market tools.
What Freshchat data does Erathos sync to Databricks?
Erathos syncs Tickets, Interactions, Agents, SLAs, Tags, and Customer Satisfaction Scores (CSAT) from Freshchat to Databricks. Custom ticket fields and support categories are also exported automatically.
How often does Erathos synchronize data from Freshchat to Databricks?
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 Freshchat pipeline efficient and Databricks costs predictable.
What happens if a Freshchat synchronization fails?
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.
Is there a free trial period for the Freshchat connector?
Yes. Every Erathos connector includes a 14-day free trial. Connect Freshchat to Databricks and start syncing immediately—no credit card required.