# Neo4j + BigQuery > Replicate data from Neo4j to BigQuery incrementally and securely. Real-time synchronization with schema drift detection and comprehensive logs. Erathos. Source: https://www.erathos.com/en/pipelines/neo4j-bigquery Em português: https://www.erathos.com/pipelines/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. ## Data in your data warehouse in minutes ### 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. ## 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. ## 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.