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@amotl
Created May 16, 2025 18:02
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How do I optimally synchronize data between MongoDB and CrateDB?

To optimally synchronize data between MongoDB and CrateDB, you should use a Change Data Capture (CDC) integration, which is available as a managed feature in CrateDB Cloud. This allows you to keep your MongoDB data continuously and efficiently synchronized with a table in CrateDB. Here’s a concise guide on how to do this:


1. Use CrateDB Cloud’s MongoDB CDC Integration

CrateDB Cloud (preview feature, see docs) can continuously import and sync data from MongoDB (e.g., MongoDB Atlas) using Change Streams.

Key Features:

  • Initial snapshot: Efficiently imports all existing data from MongoDB.
  • Continuous sync: Captures and syncs all changes (inserts, updates, deletes) in near real-time using Change Streams.
  • Schema evolution: New fields from MongoDB documents can be dynamically added in CrateDB.
  • Full document mode: Ensures strong consistency and completeness.

2. Steps to Set Up the CDC Integration

a. Prepare MongoDB Atlas:

  • User setup: Create a dedicated user with the required permissions (find, changeStream, collStats) for the collections you want to sync.
  • IP Whitelist: Add CrateDB Cloud's public IP addresses to the MongoDB Atlas access list so the sync process can connect.
  • Connection string: Copy the MongoDB connection string (including credentials) for CrateDB to access your MongoDB.

b. Configure Sync in CrateDB Cloud UI:

  1. Go to "Integrations" > "Create Integration" > "MongoDB."
  2. Enter MongoDB connection details: Host, port, database, credentials, etc.
  3. Select the database and collection you want to sync.
  4. Choose a CrateDB table name: Data will be stored in an OBJECT column (usually called document).
  5. Select synchronization mode:
    • Full Load Only (one-off import)
    • Full Load and CDC (import + ongoing sync) [recommended]
    • CDC Only (for already-imported data)
  6. Column type: Pick DYNAMIC (recommended) for better performance. Use IGNORED only if you expect large schema variability.
  7. Start the integration. The job will import all data, then keep up in real time.
  8. Monitor the sync job and check the imported tables for data.

3. Best Practices

  • Index your MongoDB source collections in Atlas for performance, especially the _id field.
  • Monitor sync lag in the CrateDB Cloud console and resolve any connectivity issues promptly.
  • Design downstream CrateDB schemas to take advantage of flexible schema/object storage, but for analytics, consider flattening commonly-used fields into top-level columns.
  • Use DYNAMIC object columns unless your data schema is extremely unstructured.
  • If needed, supplement with scheduled re-import scripts for massive historical backfills or missed change windows.
  • Consider sync direction: The CrateDB CDC is one-way (Mongo → CrateDB, not reverse).

4. Example Use Cases

  • Operational analytics: Ingest and analyze live operational data from MongoDB applications in CrateDB with near-real-time freshness.
  • Reporting dashboards: Use CrateDB as the OLAP backend for visualization (e.g., Grafana).
  • Data warehousing: Consolidate multiple MongoDB collections into a single analytical platform.

5. Useful References


Summary Table

Step Action
1. Prepare MongoDB User, Role, Network, Change Streams enabled, Connection String
2. Configure CrateDB Cloud Add MongoDB CDC Integration, map source 💾 to target table
3. Monitor Use Cloud Console; handle schema changes & sync errors as they arise
4. Query Data Use SQL to analyze JSON/object data in CrateDB

Note: If you're running CrateDB "on-prem" (not in the cloud), you’ll need to build a custom CDC pipeline (e.g., with Debezium + Kafka Connect, or a custom app) because the built-in managed CDC integration is only available in CrateDB Cloud.


In summary: For optimal, low-maintenance sync and real-time analytics, use the built-in MongoDB CDC integration in CrateDB Cloud. It's designed for reliability, scalability, and low latency for most production analytics use cases.

@amotl
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amotl commented May 16, 2025

The output above has been created with cratedb-about, cratedb-outline.yaml, llms-full.txt, and gpt-4.1.

cratedb-about ask "How do I optimally synchronize data between MongoDB and CrateDB?"

@amotl
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amotl commented May 16, 2025

Compared to other's instructions, ...

Providing instructions is crucial for guiding the behavior of your AI assistant when interacting with the Flux MCP Server. We've created a set of instructions (see instructions.md, 1400 tokens) that you can use as a starting point.

... the huge collection of knowledge conveyed through CrateDB's llms-full.txt weighs in rather heavy, with a token usage on OpenAI of:

{"input": 212817, "output": 1139, "total": 213956}

This clearly indicates an MCP server is needed to reduce token spend.

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