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PostgreSQL · logical replication

Replicate PostgreSQL to your cloud warehouse.

Describe the sync in plain English, approve it once, and rsync.ai streams every change from PostgreSQL into BigQuery, Databricks, or MySQL — read straight from the write-ahead log via logical replication, in near real time and with no polling.

Real-time logical replicationYou approve every syncNo per-row pricing
Connect PostgreSQL free →See how a sync runs
Reads the Postgres WAL — no polling You approve before anything moves
Destinations

Send PostgreSQL data where your team already works.

Pick where it lands. rsync.ai maps Postgres types automatically and builds the pipeline — you approve the plan before anything moves.

Cloud warehouse

Land typed, query-ready tables for BI and analytics — incremental after the first snapshot.

BigQueryDatabricksSnowflakeRedshift

Another database

Replicate Postgres into MySQL — or into a fresh Postgres for a migration — with automatic type mapping and real-time CDC.

MySQLPostgreSQL

Storage, lake & sheets

Write Parquet, JSON, or CSV to object storage for your lake, or push query results to a live spreadsheet.

Amazon S3GCSAzure BlobGoogle Sheets
What syncs

Every PostgreSQL object, mapped to typed columns.

Tables
Views
Primary keys
Logical replication · WAL
Snapshot + incremental
JSONB → JSON
UUID → STRING
TIMESTAMPTZ → TIMESTAMP
How it works

Four steps. Nothing runs until you approve.

01

Describe it

Name the tables to replicate in plain English — no SQL, no replication-slot setup, no connector config.

02

Review the plan

rsync.ai discovers the schema, maps Postgres types to the destination, and scans columns for likely personal data before a row moves.

03

Approve

Nothing runs until you say yes. Later schema changes are applied and recorded; only a dropped table waits for you.

04

Stream

rsync.ai subscribes to the WAL and keeps the destination up to date continuously; a failed run resumes from its last committed LSN.

After it lands

Then work with the data without leaving rsync.ai

Synced tables become something you can query, schedule and share in the same workspace.

SQL Explorer

Run SQL against your connections, with personal columns masked in previews; writes are gated by role and every write is audited.

SQL Explorer docs→

Models

Turn a query into a table that rebuilds on a schedule or when its inputs refresh, with version history and data checks.

Models docs→

Charts and Dashboards

Draw a model or saved query as a chart, then put charts on one live dashboard.

Charts→ · Dashboards→

Workflows and Ask rsync.ai

Schedule reports and data alerts to Slack or email. Describe one in plain English and Ask rsync.ai drafts it.

Scheduled reports→ · Ask rsync.ai→

Compare

Why teams move PostgreSQL this way.

What you care aboutpg_dump / cronAWS DMSPer-row ETLrsync.ai
Set up without an engineerNoConsole formsRarelyPlain English
Real-time logical replicationBatch dumpsYesVariesYes
Types mapped automaticallyBy handPartialSometimesAutomatic
You approve before it runsn/aNoNoYes
Cost as volume growsYour timePer hour + I/ORises per rowPer GB, not per row

Straight about status: the PostgreSQL source and its MySQL, BigQuery, Databricks, storage, and Google Sheets destinations are live in production. Snowflake and Redshift are in preview. Self-hosting in your own VPC is available now — source-available under the rsync.ai Source-Available License — or run rsync.ai as a managed cloud.

FAQ

PostgreSQL replication — common questions

How fresh is the data?
You choose the schedule, from a few times a day down to near real time. rsync.ai subscribes to PostgreSQL logical replication (the pgoutput plugin, built into Postgres 10+), so it receives every INSERT, UPDATE, and DELETE for the tables you selected in near real time — no polling, no watermark queries. A failed run resumes from its last committed LSN instead of starting over.
Does CDC work on Amazon RDS, Aurora, and Azure Database for PostgreSQL?
Yes. On RDS and Aurora, set rds.logical_replication=1 in the parameter group, then reboot; on Azure Database for PostgreSQL, set the replication support (azure.replication_support) server parameter to logical and restart. rsync.ai creates the publication and replication slot for you; the connecting user needs the REPLICATION attribute. rsync.ai uses pgoutput, which is built into PostgreSQL. On self-managed PostgreSQL, set wal_level=logical (a restart is required) and rsync.ai subscribes. Minimum supported version is PostgreSQL 10.
What do I need to set up on PostgreSQL before connecting?
A user with replication privileges, wal_level=logical (changing it needs a restart), and max_replication_slots and max_wal_senders of at least 1. rsync.ai creates the replication slot and publication for you. Tables replicated into PostgreSQL or MySQL need a primary key. rsync.ai runs a pre-flight check and tells you what is missing before anything starts.
How much WAL disk will the replication slot use, and what if rsync.ai goes down?
A replication slot retains WAL segments until rsync.ai confirms it has processed them, so no changes are lost during an outage. To protect against disk exhaustion in a long outage, set max_slot_wal_keep_size (Postgres 13+) to a safe limit — typically 5–20 GB depending on write volume. rsync.ai checkpoints its LSN frequently, so in normal operation WAL retention stays minimal. Postgres destinations commit the offset in the same transaction as the data, so a restart does not write duplicates; warehouse and object-store destinations apply changes idempotently.
Do I need to write SQL or configure a connector?
No. Describe the sync in plain English. rsync.ai discovers the schema, maps Postgres types to the destination — JSONB, UUID, TIMESTAMPTZ, NUMERIC, arrays, and more — scans columns for likely personal data, and shows you the plan. Nothing runs until you approve it, and you can mask or hash sensitive columns (SHA-256) before they reach the destination.
How are you priced?
On data volume (GB moved), not per row or Monthly Active Rows. Each plan includes a monthly GB allowance (10 GB on the free month), and pipelines pause at your cap instead of running up charges.
Who controls what moves?
You do. No pipeline is created or started until you confirm the plan, PII rules apply before data lands, and later schema changes are applied and recorded (only a dropped table waits for a person). Self-hosting entirely in your own VPC is available now for teams that need data to never leave their network.

Put your PostgreSQL data in the warehouse.

Connect your database free and send your first live sync to BigQuery or Databricks today.

Connect PostgreSQL free →See how it works
Live on rsync.ai Cloud today · self-hosted (rsync.ai Source-Available License)