AgendorAzure SQL Server

Agendor + Azure SQL Server

Agendor is a CRM platform for sales management and customer relationships that allows tracking sales funnels and organizing contacts. Azure SQL Server, on the other hand, is a relational database service by Microsoft that provides robust storage and large-scale data analysis capabilities.

With Erathos, you can integrate Agendor data into Azure SQL Server in just a few minutes. Our platform handles the entire data movement process to your analytical environment, allowing you to blend this data with other sources in your Data Warehouse. This frees up your time to focus on what actually drives value — extracting powerful insights and making more data-driven decisions.

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Ace Startups
Kamino
Convenia
Vakinha
Linus
Rabbot
Auvo
Roqt
Xperiun
Tecnova
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.

What Agendor data does Erathos sync to Azure SQL Server?

The integration automatically syncs the main objects from Agendor:

  • Contacts — emails, lifecycle stages, and custom properties
  • Companies — firmographic data, industry, and activity history
  • Deals — pipeline stages, deal values, and close dates
  • Activities — calls, meetings, tasks, and sales team notes
  • Interaction history — emails, calls, and engagement logs
  • Custom fields — automatically included properties created by your team

Why sync Agendor with Azure SQL Server?

In Azure SQL Server, you integrate Agendor data into the Microsoft ecosystem, using Power BI for executive dashboards and Azure Data Factory for broader pipeline orchestration.

How it works

Erathos connects to Agendor via official API and syncs your data incrementally — only new or updated records are processed on each run, keeping pipelines fast and Azure SQL Server costs predictable. You choose the sync frequency (from every 5 minutes to daily), the objects to sync, and the destination dataset. Every run is logged with full observability: runtime, rows processed, errors with context, and instant alerts via Slack or email if something goes wrong.

Why companies move data from Agendor to Azure SQL Server with Erathos

Centralizing Agendor data into Azure SQL Server has never been easier

Erathos is a data ingestion platform built for teams that demand reliability, visibility, and control. With the Agendor connector, you can automatically move contacts, deals, companies, and sales activities to Azure SQL Server — featuring full observability for every execution and zero maintenance.

Why data teams choose Erathos for Agendor?

Data in your data warehouse in minutes

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Our partners

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 Agendor to their data warehouse — with full observability of every run, zero maintenance, and without the opacity of traditional market tools.

Erathos syncs key Agendor objects: Contacts, Companies, Deals, Activities, Tasks, and Interaction History. Custom fields created by your team are also supported and automatically made available in Azure SQL Server.

You can configure the sync frequency from every 5 minutes to daily, at the table level. Erathos uses incremental sync — only new or updated records are processed in each run, keeping the Agendor pipeline efficient and Azure SQL Server 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 run is logged with runtime, rows processed, and error context so your team can debug in minutes, not hours.

Yes. Every Erathos connector includes a 14-day free trial. Connect Agendor to Azure SQL Server and start syncing immediately — no credit card required.

Data ingestion with control, observability and scale