Estuary is the pick for Postgres to Snowflake replication when you need Snowflake freshness below one minute. It is also the pick when the bill must follow captured and delivered data volume. Fivetran fits teams whose same rows update repeatedly each month and who can use sync intervals set by their plan.
Postgres to Snowflake: Estuary vs Fivetran at a Glance
Estuary streams Postgres changes to Snowflake and lets you set the delivery schedule, including pushing updates as fast as the destination allows. It charges for data captured and delivered, plus connector instances. Fivetran syncs at intervals determined by your plan and bills by monthly active row (MAR).
Estuary's Cloud plan charges $0.50 per GB plus $100 per connector instance per month, as of October 2026. Instances after the sixth cost $50 each. Its published example for 100 GB from Postgres to Snowflake counts 200 GB and two connector instances for $300 a month.
Fivetran bills connections and activations in monthly active rows, or MAR. It defines MAR as distinct rows synced to a destination in a calendar month. With stable primary keys and history mode disabled, Fivetran counts an active row once per month, regardless of how many times it is updated.
That distinction matters most for tables with heavy update churn. A row updated many times counts once under Fivetran's MAR model, while Estuary counts captured and delivered volume.
How Estuary and Fivetran Replicate Postgres to Snowflake
Both tools read Postgres changes from the write-ahead log. The comparison starts with what each product asks of your Postgres database.
How does Estuary replicate Postgres to Snowflake?
Estuary's PostgreSQL capture connector uses change data capture to continuously capture updates from a PostgreSQL database into one or more collections. The setup requires logical replication enabled at the database level. Estuary reads change events through a PostgreSQL replication slot, which acts as a cursor into the write-ahead log.
Managed PostgreSQL instances that do not support logical replication can use Estuary's PostgreSQL Batch Connector instead. Teams that need private or bring-your-own-cloud deployment also need an annual or multi-year Enterprise contract.
The setup choices narrow the list. Confirm that your Postgres platform supports logical replication, or plan to use the Batch Connector. Add an Enterprise contract if the pipeline needs private or BYOC deployment.
How does Fivetran replicate Postgres to Snowflake?
Fivetran's PostgreSQL connector replicates data from PostgreSQL to a destination. Its logical replication mode reads changes from the PostgreSQL write-ahead log, and Fivetran recommends that mode for large PostgreSQL databases. Query-Based sync is the fallback when logical replication is not an option.
During setup, a database administrator creates the Fivetran user and grants it the required permissions.
Fivetran supports SaaS and Hybrid deployment for all PostgreSQL implementations. Hybrid Deployment requires an Enterprise or Business Critical plan.
For log-based CDC, both tools require logical replication to be enabled in Postgres. Each reads changes through its own replication slot using a database user with replication privileges.
Estuary vs Fivetran: Postgres to Snowflake Comparison
The table compares how Estuary and Fivetran capture Postgres changes, deliver them to Snowflake, and bill for the pipeline. Read the table across each row from Postgres capture through schema handling and best-fit team.
| Vendor | Postgres capture | Delivery floor | Snowflake write path | Billing unit | Setup and operations | Schema handling | Best-fit team |
|---|---|---|---|---|---|---|---|
| Estuary | CDC through a logical replication slot; batch connector available as a fallback | A 0s delivery interval pushes changes as fast as Snowflake allows | Stages changes and applies them transactionally; Snowpipe Streaming is available for delta updates | $0.50 per GB captured or delivered, plus $100/month for each of the first six connector instances | CDC requires logical replication; private and BYOC deployments require an Enterprise contract | AutoDiscover can evolve breaking changes; the affected destination table is backfilled | Teams that need continuous capture and control over delivery timing |
| Fivetran | Logical replication through a replication slot; query-based sync available as a fallback | Shortest scheduled interval: 15 minutes on Standard; 1 minute on Enterprise and Business Critical | Uses SQL to merge changes into native Snowflake tables | Monthly active rows (MAR), counted per connection | Logical replication requires a user with replication privileges; Hybrid Deployment requires Enterprise or Business Critical | Some Postgres schema changes require a table re-sync | Teams whose data changes repeatedly on the same keys and whose freshness needs fit the scheduled interval |
Delivery cadence: Estuary schedules and Fivetran sync frequency
Estuary controls destination sync cadence on the materialization side (Estuary sync schedule). Capture runs as change data capture, while the materialization controls the destination sync cadence. The default 30-minute interval batches writes to Snowflake, which can reduce warehouse compute costs. If you need fresher data, set the interval to 0s to remove the scheduled wait and push changes as fast as Snowflake can accept them.
Estuary also says its platform delivers data in under 100 milliseconds end-to-end. Treat that number as Estuary's platform statement rather than an independent benchmark.
Fivetran’s default is a fixed six-hour interval (Fivetran sync overview). Fivetran’s shortest scheduled sync interval is 15 minutes on Standard and one minute on Enterprise and Business Critical.
Estuary pricing versus Fivetran monthly active rows
Estuary's Cloud plan charges $0.50 per GB plus $100 per connector instance per month, as of October 2026. Instances after the sixth cost $50 each. Estuary's pricing page counts data each time it is captured and each time it is delivered. Its 100 GB Postgres to Snowflake example therefore counts 200 GB, plus two connector instances, for $300 a month.
That example makes the meter easy to estimate for a single destination. The bill moves with captured volume, delivered volume, and the number of connector instances.
Use Estuary's example as a format for your own calculation, not as a quote for your pipeline. Replace its inputs with your captured GB, delivered GB, and connector count.
Fivetran measures connection and activation usage in MAR. It defines MAR as the distinct rows synced to a destination in a calendar month. With stable primary keys and history mode disabled, Fivetran counts an active row once per month, no matter how many times it is updated.
Fivetran also applies a $5 base charge to standard connections with monthly usage between 1 MAR and one million MAR, as of October 2026.
Suppose a Postgres table receives 100 GB of new rows in a month. At an average of 1 KB per row, using decimal units and a distinct primary key for each row, that’s about 100 million monthly active rows. Fivetran Standard’s list price comes to about $2,894. In Estuary’s Postgres-to-Snowflake example, the same pipeline costs $300: $100 for 200 GB of total billed data (100 GB captured + 100 GB delivered), plus $200 for two connector instances. Both figures exclude Snowflake charges.
Frequent updates to the same rows can change the comparison. With stable primary keys and history mode disabled, Fivetran counts each active row only once per month. Estuary bills for the bytes it captures and the bytes it processes for delivery, including repeat changes.
The cost decision follows the shape of the workload. With stable primary keys and history mode disabled, Fivetran’s MAR meter counts each distinct row once, so repeated updates do not add MAR. Estuary, by contrast, counts each change’s bytes on capture and again on delivery.
Estimate Fivetran from distinct primary keys per month, not from the number of change events. Estimate Estuary from captured GB, delivered GB, and connector instances.
How each tool writes to Snowflake
Estuary's Snowflake connector supports standard and delta updates, with Snowpipe Streaming available for delta bindings. It first uploads data changes to a Snowflake table stage, then transactionally applies them to the table. Standard updates are the default.
Estuary says the resulting table in Snowflake will not be fully reduced. Use the default standard merge for a current-state table. Choose delta updates only when the pipeline expects the destination to hold changes rather than a finished current-state view.
Fivetran loads Snowflake tables with SQL queries that merge data into them (Fivetran Snowflake destination). It recommends an X-Small Snowflake warehouse with one-minute auto-suspend for its loads. Fivetran says most customers are billed for 10 to 20 percent usage of an X-Small warehouse, and that more frequent syncs increase that usage.
Fivetran’s MERGE loads consume Snowflake warehouse credits. Estuary can use Snowpipe Streaming for delta bindings to load rows without using your warehouse, though Snowflake still charges for streaming ingestion.
Estuary defaults to standard updates and also offers delta updates and Snowpipe Streaming for teams that want them. Fivetran loads with SQL MERGE and documents a small warehouse configuration and the compute effect of more frequent syncs.
Schema changes and DDL failure modes
With AutoDiscover configured to handle breaking changes, Estuary can evolve the schema automatically. The affected Snowflake table is then backfilled from the beginning, so teams should account for the time and warehouse compute that takes.
Fivetran documents gaps in logical replication (Fivetran DDL support). Fivetran says logical replication does not replicate all DDL changes, and an added column with a default is not recognized. Its DDL table marks a change as No when the change is not reflected in the destination and requires a table re-sync.
Verdict: pick Estuary or Fivetran
Pick Estuary when Snowflake freshness must fall below one minute. Pick it when the pipeline needs automated schema evolution or a bill that follows captured and delivered GB. Estuary's 0s schedule pushes updates as fast as possible, and AutoDiscover triggers schema evolution for breaking changes.
Pick Fivetran when the same primary keys update many times a month, and MAR billing matches that pattern. Choose it when a one-minute sync on an Enterprise or Business Critical plan meets the freshness requirement. With stable primary keys and history mode disabled, MAR billing counts each distinct row once a month, regardless of how many times it changes.
Before choosing Fivetran for a large Postgres table, estimate MAR from the distinct primary-key count per month. Do not estimate it from the number of updates, because Fivetran counts a row once per month.
Before choosing either tool, measure two weeks of change volume, distinct rows, and required freshness on the same Postgres source.
Record captured change volume, delivered change volume, distinct primary keys, and the p95 delay from commit in Postgres to a query in Snowflake. Keep Snowflake warehouse credits as a separate line, and hold the source snapshot and query workload constant across trials.
FAQ
Five questions cover sync frequency, pricing units, schema changes, and the managed setup path.
Does Fivetran sync Postgres to Snowflake in real time?
No. Fivetran's default is every six hours. Fivetran syncs at fixed intervals from one minute to six hours.
How often does Estuary sync Postgres changes to Snowflake?
Estuary captures Postgres changes continuously. By default, it
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