One-click data pipelines for Apache Airflow to MongoDB
Easily sync data from Apache Airflow to MongoDB, explore your data with the rich Data Explorer and transform your Apache Airflow data with SQL.
- 5-minute setup
- GDPR compliant, EU-hosted
- SOC 2 Type II certified
Apache Airflow to MongoDB, end to end
Apache Airflow
Apache Airflow is a SaaS application used in modern business operations, holding valuable data on customers, transactions, or workflows. Getting Apache Airflow data out for cross-source analytics typically requires custom scripts or one-off integration tools. Peliqan provides a managed Apache Airflow connector that syncs data into your warehouse automatically, unlocking cross-source reporting, AI use cases, and reverse ETL workflows.
MongoDB
MongoDB is the most popular NoSQL document database, used widely for application backends, content systems, and use cases where schema flexibility matters more than relational structure. Loading MongoDB from SaaS applications normally means writing custom services. Peliqan provides managed MongoDB connectors that sync data into collections with schema flattening and incremental updates.
Common Apache Airflow to MongoDB use cases
Instant ELT pipeline & data warehouse loading
Peliqan brings ETL pipelines, data transformations and reverse ETL together in one integrated platform. Connect your favorite BI tool and activate your data with SQL and low-code Python.
Direct-to-warehouse sync
Sync Apache Airflow data into MongoDB in a few clicks. Want another target? Point the same pipeline at Peliqan’s built-in warehouse or any database you run.
One-click pipeline setup
Set up a production-ready ELT pipeline in just minutes. Apache Airflow data lands in MongoDB with schema detection, incremental syncs from every 15 minutes.
AI-driven data management
Transform Apache Airflow data in MongoDB using SQL or low-code Python. Describe the logic in plain English, let AI draft it, then clean, validate and enrich.
Multi-source integration
Combine Apache Airflow with any of Peliqan’s 300+ connectors inside MongoDB. Build unified data sets for analytics, reporting and AI in one place, not five tools.
Python & SQL processing
Write your own Python or SQL when you need control. Schedule scripts, enforce business rules and publish Streamlit data apps on Apache Airflow data in MongoDB.
Reverse ETL & orchestration
Push enriched MongoDB data back into the apps your teams use, then run the whole flow on a schedule with built-in orchestration, dependencies and alerts.
How to connect Apache Airflow and MongoDB
1. Connect in 30 Seconds
Authenticate your source (Apache Airflow)
via OAuth or API key – no complex setup.
2. Data Flows Automatically
Your data appears in the Peliqan data warehouse with automatic schema detection and optimization for analytics.
Or bring your own data warehouse (Snowflake, Redshift, Bigquery, Clickhouse, Fabric).
3. Query & Analyze
Use SQL, natural language queries, or the Peliqan data explorer and analyze your unified data.
4. Activate Insights
Connect your favorite BI tool to the Peliqan data warehouse, build Python apps, and sync insights back to your business applications.
5. Enable AI Agents
Turn on AI Agents (RAG and text-to-SQL) to answer business queries, generate SQL, or trigger downstream actions (e.g., create a CRM task).
Beyond simple sync
A cloud data platform designed for the systems and workflows modern data and business teams use every day.
Incremental pipelines
Efficiently sync only new & changed records from Apache Airflow to MongoDB using incremental loading strategies.
Schema evolution management
Automatically handle schema changes in Apache Airflow – new fields, renamed columns, and type changes are detected and propagated to MongoDB.
Data quality & validation
Built-in data quality checks ensure clean data in MongoDB. Set validation rules, detect anomalies, and get alerts for data quality issues.
Enterprise orchestration
Schedule complex workflows, dependencies, and multi-step pipelines. Use built-in orchestration capabilities.
Warehouse-native optimization
Loads are tuned to MongoDB using its native bulk-load path for optimal query performance.
Developer platform
REST APIs, Python SDK and a custom connector framework for advanced data engineering workflows.
What Peliqan syncs from Apache Airflow
Peliqan loads your Apache Airflow data into MongoDB as analytics-ready tables you can query with SQL. Schema changes are handled automatically.
The Apache Airflow connector is live. We have not published its table list on this page yet, so the documentation has the current schema.
Technical Specifications
Peliqan provides a high-performance ELT engine optimized for modern cloud data warehouses.
Load, transform and orchestrate data reliably with warehouse-native speed and security.
Supported Data Types
- Protocols – REST, SOAP, SFTP, ODBC, JDBC etc.
- Support for staging tables, external tables & native ingestion formats
- Automatic schema evolution and change detection
Performance & scale
- Handles millions of records with distributed processing
- Near real-time data sync for most object types
- 99.9% uptime SLA with redundant infrastructure
Security features
- End-to-end encryption in transit and at rest
- VPN tunnel support and on-premises agents
- Enterprise SSO integration available
More destinations for Apache Airflow
Send data out
Sync your Apache Airflow data into these databases and warehouses.
SaaS Data Cockpit
Connect your apps, then work with the data in a spreadsheet, in SQL, or in plain English. No pipelines to maintain.
Built with enterprise-grade security and compliance.
Frequently asked questions
Can I connect multiple Apache Airflow instances?
Yes, you can connect multiple instances of Apache Airflow and unify the data, or you can customize field mappings for each connection.
How often does the data sync?
You control the sync frequency: as often as every 15 minutes on the Pro plan, or hourly, daily and custom schedules. Some source systems set their own limits – Exact Online, for example, defaults to every 6 hours.
Can I transform data during the sync process?
Yes. Transform data with SQL or low-code Python before or after it lands in the warehouse. You can clean fields, join across sources and reshape tables without touching the source system.
Is there a limit on data volume?
Peliqan handles enterprise-scale data volumes. Our distributed architecture processes millions of records efficiently with automatic scaling based on your needs.
What if I need a custom integration?
Our team builds custom connectors, typically within 2 weeks. You can also build your own pipelines with low-code Python.
Ready to run Apache Airflow reports on live data in MongoDB?
Connect Apache Airflow to MongoDB in minutes, and build the reports and dashboards your team actually needs.