Neo4jDatabricks

Neo4j + Databricks

Neo4j is a graph database management system, designed to store and query highly connected data by efficiently modeling relationships between entities. Databricks, in turn, is a serverless Big Data solution that delivers robust storage and large-scale analytics capabilities.

With Erathos, you can integrate data from Neo4j into Databricks in just a few minutes. Our platform handles the entire data movement process into your analytics environment and lets you combine that data with other sources in your Data Warehouse. That way, your time goes where it really creates value — extracting actionable insights and making more data-driven decisions.

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Trusted by great companies

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 Neo4j data does Erathos sync with Databricks?

The integration automatically syncs Neo4j's core objects:

  • Selected tables — incremental replication of any configured table
  • Schema drift — new columns detected and automatically added to the destination
  • Primary keys and timestamps — used for efficient incremental syncing
  • Historical data — full initial load followed by incremental updates

Why sync Neo4j with Databricks?

Keeping an analytical copy of Neo4j operational data in Databricks ensures heavy queries don't impact production application performance. With incremental replication and schema drift detection, your data warehouse stays up to date while the transactional database remains stable and responsive.

How it works

Erathos connects to Neo4j through the official API and syncs 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 5 minutes to daily), the objects to sync, and the destination dataset. Every run is logged with full observability: run time, processed rows, contextual errors, and instant alerts via Slack or email if something goes wrong.

Why Companies Move Data from Neo4j to Databricks with Erathos

Centralizing Neo4j data in Databricks has never been easier

Erathos is a data ingestion platform for teams that need to replicate operational databases for analytics. With the Neo4j connector, you can incrementally sync tables and transactional records to Databricks—with schema drift detection and complete logs for every run.

Why do data teams choose Erathos for Neo4j?

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 Neo4j to their data warehouse—with full observability into every run, zero maintenance, and none of the opacity of traditional market tools.

Erathos uses incremental replication to synchronize Neo4j tables to Databricks. Schema drift is detected automatically—if a column is added or changed in Neo4j, the pipeline adapts without manual intervention.

You can configure 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 Neo4j 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 Neo4j to Databricks and start syncing immediately—no credit card required.

Data ingestion with control, observability and scale