Neo4j + BigQuery
Neo4j is a graph database management system designed to store and query highly connected data, efficiently representing relationships between entities. Postgres, on the other hand, is a highly robust and scalable open-source relational database management system that supports a wide range of data types and advanced features.
With Erathos, your Neo4j data reaches BigQuery in minutes, ready to be joined with other business sources in ad hoc queries, without your team having to manage ingestion infrastructure.
What Neo4j data does Erathos sync with PostgreSQL?
The integration automatically syncs key Neo4j objects:
Selected tables incremental replication of any configured table
Schema drift new columns are automatically detected and added to the destination
Primary keys and timestamps used for efficient incremental syncs
Historical data full initial load followed by incremental updates
Why sync Neo4j with BigQuery?
In BigQuery, you can query your Neo4j data alongside other business sources, running ad hoc queries in seconds over large volumes without managing any infrastructure.
How it works
Erathos connects to Neo4j via the official API and syncs your data incrementally: only new or updated records are processed in each run, keeping pipelines fast and BigQuery costs predictable. You choose the sync frequency (from 5 minutes to daily), the objects to sync, and the target dataset. Each run is logged with full observability: execution time, rows processed, error context, and instant alerts via Slack or email if anything goes wrong.
No credit card required.
Why do data teams choose Erathos for Neo4j?
Ready-to-use Neo4j connector
Replicate Neo4j tables to BigQuery with incremental synchronization and automatic schema drift detection—without breaking pipelines when the structure changes.
Total control over your Neo4j pipelines
Configure schedule, frequency, and sync type at the table level. Incremental synchronization processes only new or modified records—keeping BigQuery costs low and your analyses always up to date.
End-to-end observability
No more finding out about Neo4j failures when the business team complains. Every run is logged with runtime, processed rows, and error context. Automatic alerts via Slack, Discord, or email as soon as something goes off track — keeping replication up to date without impacting the transactional database.
Why companies move data from Neo4j to BigQuery with Erathos
Centralizing Neo4j data in BigQuery 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 BigQuery — with schema drift detection and complete logs for every run.
Our Customers
1
Bruno Rosso
Data Analyst
Every new source implementation, if I had to do it alone, would take me about two or three months. With Erathos, it's done in a few hours. I don't need a data engineer's skillset to deliver real value with company data.
10
Luis Ribas
CTO
I can describe my experience with Erathos as seamless; we had no major issues migrating from our old data pipeline platform. Their support is always impeccable, both in answering questions and resolving issues. I highly recommend them, without a doubt.
11
Sayuri Valente
Project Manager
The robustness and efficiency of Erathos's connectors—whether for Meta, Google, RD Station, or ERPs like Bling and Conta Azul—make the entire pipeline much faster and more reliable. The technical documentation is extremely well-crafted and intuitive, which greatly legacy simplifies implementation.
2
Kauê Raizer
Co-founder
Centralizing our data with Erathos gave us a roadmap to structure the company: today, we can view NPS and churn in a consolidated way and use that to drive decisions. If I were to give advice to another founder, it would be: centralize your data from day one.
3
Matheus Nunes
CTO & Co-founder
Erathos revolutionized data management at WE. By integrating multiple SaaS platforms into a single DW, our engineering team can now focus on the core business. We implemented dashboards providing insights across all departments, enriching our data culture and streamlining decision-making.
4
Fernando R.
Head of Data
Erathos brought an incredible boost in productivity. With no worries about data ingestion, the team focused on strategy rather than pipeline maintenance. Implementing a new connector takes minutes, and the reliability is outstanding. It was one of the best decisions we've made.
5
Carlos Schwabe
Co-Founder & CDO
We used to have a lot of rework, but not anymore. Working this way is much more efficient. If it's not your core business, hire Erathos. Spend your time modeling your own domain, not someone else's.
6
Fernando Costa
CTO & Co-founder
It was impossible to run our operations on spreadsheets. Erathos was a perfect fit: they became the data engineer I didn't have. We managed to reduce analysis time, establish weekly data rituals, and, most importantly, trust the data we use.
7
Thiago Paz
CFO
If I didn't have this infrastructure, I would need three or four people to do what Erathos does today. I was able to drive real value from my data with a much leaner team than I ever imagined needing.
8
Felipe Corrêa
CTO & Co-founder
Erathos is essential for anyone looking for a quick go-live when centralizing data from multiple sources. We successfully integrated 6 different data sources in a single day, something that would have taken weeks without Erathos.
1
Bruno Rosso
Data Analyst
Every new source implementation, if I had to do it alone, would take me about two or three months. With Erathos, it's done in a few hours. I don't need a data engineer's skillset to deliver real value with company data.
10
Luis Ribas
CTO
I can describe my experience with Erathos as seamless; we had no major issues migrating from our old data pipeline platform. Their support is always impeccable, both in answering questions and resolving issues. I highly recommend them, without a doubt.
11
Sayuri Valente
Project Manager
The robustness and efficiency of Erathos's connectors—whether for Meta, Google, RD Station, or ERPs like Bling and Conta Azul—make the entire pipeline much faster and more reliable. The technical documentation is extremely well-crafted and intuitive, which greatly legacy simplifies implementation.
2
Kauê Raizer
Co-founder
Centralizing our data with Erathos gave us a roadmap to structure the company: today, we can view NPS and churn in a consolidated way and use that to drive decisions. If I were to give advice to another founder, it would be: centralize your data from day one.
3
Matheus Nunes
CTO & Co-founder
Erathos revolutionized data management at WE. By integrating multiple SaaS platforms into a single DW, our engineering team can now focus on the core business. We implemented dashboards providing insights across all departments, enriching our data culture and streamlining decision-making.
4
Fernando R.
Head of Data
Erathos brought an incredible boost in productivity. With no worries about data ingestion, the team focused on strategy rather than pipeline maintenance. Implementing a new connector takes minutes, and the reliability is outstanding. It was one of the best decisions we've made.
5
Carlos Schwabe
Co-Founder & CDO
We used to have a lot of rework, but not anymore. Working this way is much more efficient. If it's not your core business, hire Erathos. Spend your time modeling your own domain, not someone else's.
6
Fernando Costa
CTO & Co-founder
It was impossible to run our operations on spreadsheets. Erathos was a perfect fit: they became the data engineer I didn't have. We managed to reduce analysis time, establish weekly data rituals, and, most importantly, trust the data we use.
7
Thiago Paz
CFO
If I didn't have this infrastructure, I would need three or four people to do what Erathos does today. I was able to drive real value from my data with a much leaner team than I ever imagined needing.
8
Felipe Corrêa
CTO & Co-founder
Erathos is essential for anyone looking for a quick go-live when centralizing data from multiple sources. We successfully integrated 6 different data sources in a single day, something that would have taken weeks without Erathos.
Trusted by data-driven companies
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 the purpose of the Neo4j BigQuery integration with Erathos?
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.
How does Erathos sync data from Neo4j to BigQuery?
Erathos uses incremental replication to sync tables from Neo4j to BigQuery. Schema drift is automatically detected—if a column is added or changed in Neo4j, the pipeline adapts without manual intervention.
How often does Erathos sync data from Neo4j to BigQuery?
You can configure the sync frequency at the table level, from every 5 minutes up to daily. Erathos uses incremental synchronization—only new or updated records are processed in each run, keeping the Neo4j pipeline efficient and BigQuery costs predictable.
What happens if a Neo4j 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 Neo4j connector?
Yes. Every Erathos connector includes a 14-day free trial. Connect Neo4j to BigQuery and start syncing right away—no credit card required.