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- <100ms Data pipelines
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- 2-5x less than batch ELT



Dropbox connector details
The Dropbox connector captures data from a specified Dropbox folder into Estuary collections, enabling automated ingestion of structured and semi-structured files for analysis and downstream use.
- Folder-based ingestion: Continuously reads and captures files from a designated Dropbox folder into Flow, keeping data pipelines updated as new files are added.
- Multi-format support: Automatically detects and parses multiple file types, including Avro, CSV, JSON, Protobuf, and W3C Extended Log formats.
- Automatic compression handling: Supports ZIP, GZIP, and ZSTD compression with optional manual override for custom configurations.
- Custom parsing control: Advanced users can explicitly define parsing rules such as delimiter type, headers, compression, and encoding for CSV or other formats.
- Efficient incremental sync: The optional Ascending Keys mode improves performance by reading only new files added since the last sync, based on lexicographic key order.
- Secure authentication: Uses OAuth2 for account access, automatically managed within the Flow web app.
💡 Tip: For the fastest incremental syncs, enable Ascending Keys only if your Dropbox data is organized with timestamped or sequentially ordered filenames.


HIGH THROUGHPUT
Distributed event-driven architecture enable boundless scaling with exactly-once semantics.

DURABLE REPLICATION
Cloud storage backed CDC w/ heart beats ensures reliability, even if your destination is down.

REAL-TIME INGESTION
Capture and relay every insert, update, and delete in milliseconds.
Real-timehigh throughput
Point a connector and replicate changes from Dropbox in <100ms. Leverage high-availability, high-throughput Change Data Capture.Or choose from 100s of batch and real-time connectors to move and transform data using ELT and ETL.
- Ensure your Dropbox insights always reflect the latest data by connecting your databases to Dropbox with change data capture.
- Or connect critical SaaS apps to Dropbox with real-time data pipelines.
Don't see a connector?Request and our team will get back to you in 24 hours
Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.
Feature Comparison
Estuary | Batch ELT/ETL | DIY Python | KAFKA | |
---|---|---|---|---|
Price | $ | $$-$$$$ | $-$$$$ | $-$$$$ |
Speed | <100ms | 5min+ | Varies | <100ms |
Ease | Analysts can manage | Analysts can manage | Data Engineer | Senior Data Engineer |
Scale |

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