Live CDC replication

Migrate MongoDB to
ClickHouse

Migrate MongoDB to ClickHouse with live CDC replication, automatic schema mapping, and zero downtime. Production-ready in minutes, not weeks.

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BSON Schema Detection

Automatically detect field types across all collections — ObjectId, ISODate, NumberInt, nested objects, and arrays — and map them to SQL equivalents.

ObjectId → UUID

MongoDB Oplog CDC

Tail the MongoDB oplog in real time. Every insert, update, and delete flows to the SQL target with sub-second latency. Zero data loss guaranteed.

< 50ms latency

Type Coercion Engine

Flexible MongoDB types don't break your schema. ISODate → TIMESTAMPTZ, NumberInt → INTEGER, Double → DOUBLE PRECISION. Custom overrides available.

Auto type mapping

Zero Downtime Cutover

Dual-write mode keeps MongoDB and the SQL target in sync during migration. Cut over when you're ready — with automatic rollback.

Dual-write mode

Incremental Sync

Migrate historical data in bulk, then keep new writes in sync via CDC. No need to pause your application. Works with collections of any size.

Bulk + streaming

Schema Validation

Before migrating, validate that every document conforms to the inferred schema. Catch type mismatches early. Drill down to individual offending documents.

Pre-flight checks
How it works

Three steps to ClickHouse

1
Connect your MongoDB
Paste your MongoDB connection string. NoSQLSync detects all collections/tables and samples documents/items to infer the full schema — including nested structures.
2
Review the schema & map columns
Our auto-mapper converts MongoDB types to ClickHouse types. Review and adjust: rename columns, change types, flatten nested structures, or use JSON/JSONB for flexible fields.
3
Launch migration & monitor
Click launch. Watch records flow in real time with throughput charts, latency metrics, and error alerts. Enable live CDC to keep your SQL target in sync until cutover.

Type mapping: MongoDB → ClickHouse

ObjectId / String IDString / UUIDString or dedicated UUID type
StringStringNative ClickHouse String
Number / IntegerInt32 / Int64Signed integer types
Double / DecimalFloat64 / DecimalFloating or decimal precision
Date / TimestampDateTime64High-precision timestamp
BooleanBoolNative ClickHouse Bool
Array / ListArray(String) / JSONTyped array or JSON
Object / Map / Nested docJSON / NestedObject as JSON or Nested type
Binary / BytesStringBinary stored as String
Null / MissingNullable(type)Nullable column wrappers

Frequently asked questions

What happens to embedded documents and arrays?

Embedded documents become JSONB columns by default, with full PostgreSQL indexing support. You can optionally flatten specific fields into their own columns using the visual schema mapper.

How are MongoDB ObjectIds handled?

ObjectIds are automatically mapped to UUID in PostgreSQL. All references and foreign key relationships are preserved. Legacy ObjectId strings can be kept in a companion column.

Can I migrate only specific collections?

Yes. Choose which MongoDB collections to migrate. Each collection becomes a separate SQL table. Filter documents with queries to migrate only a subset.

How long does a migration take?

A typical 100 GB dataset migrates in under 2 hours with bulk mode. With CDC enabled, ongoing writes sync in real time. Total time depends on data volume and network throughput.

Is my data secure during migration?

Yes. All data is encrypted in transit (TLS 1.3) and at rest (AES-256). Database credentials use short-lived tokens. Migration workers run in an isolated environment and never store data after the job completes.

Can I roll back if something goes wrong?

Yes. Dual-write mode keeps both databases in sync. If you detect issues after cutover, just reverse to the source in one click. Your original data is never modified.

Other migration paths from MongoDB

MongoDB → PostgreSQLMongoDB → MySQLMongoDB → BigQueryMongoDB → SnowflakeMongoDB → RedshiftMongoDB → SQL ServerMongoDB → MariaDB

Ready to migrate to ClickHouse?

Connect your MongoDB and ClickHouse instances. No credit card required.

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