Convert PostgreSQL to Snowflake
A free online converter that translates PostgreSQL queries into Snowflake. Paste your SQL, press Translate, and Query Studio rewrites the syntax that differs between the two databases — instantly, with no login and nothing stored.
A common analytics migration. The SQL is close, and two things reliably cause trouble: identifiers fold to upper case rather than lower, and JSONB operators have no equivalent in Snowflake's VARIANT type.
PostgreSQL → Snowflake example
Here is a real PostgreSQL query and the Snowflake output Query Studio produces:
SELECT u.id, u.name, COUNT(o.id) AS orders
FROM users u
LEFT JOIN orders o ON o.user_id = u.id
WHERE u.created_at > '2024-01-01' AND u.active = TRUE
GROUP BY u.id, u.name
HAVING COUNT(o.id) > 3
ORDER BY orders DESC
LIMIT 10;SELECT
u.id,
u.name,
COUNT(o.id) AS orders
FROM
users u
LEFT JOIN orders o ON o.user_id = u.id
WHERE
u.created_at > '2024-01-01'
AND u.active = TRUE
GROUP BY
u.id,
u.name
HAVING
COUNT(o.id) > 3
ORDER BY
orders DESC
LIMIT
10;What changes from PostgreSQL to Snowflake
- The result is re-indented and keyword-cased in Snowflake style so it's ready to paste and run.
PostgreSQL to Snowflake data type mapping
Query Studio translates queries, not schemas. When you come to move the tables themselves, this is what changes between PostgreSQL and Snowflake:
| PostgreSQL | Snowflake | Watch out for |
|---|---|---|
| TEXT / VARCHAR(n) | VARCHAR | Snowflake stores all strings the same way; a length is a constraint, not an optimisation. |
| SERIAL | NUMBER AUTOINCREMENT | Direct equivalent. |
| TIMESTAMPTZ | TIMESTAMP_TZ | Direct equivalent. |
| TIMESTAMP | TIMESTAMP_NTZ | Direct equivalent. |
| JSONB | VARIANT | VARIANT is Snowflake's semi-structured type; access is via colon notation (col:field) rather than -> and ->>. |
| TEXT[] | ARRAY | Direct equivalent. |
| INTEGER / BIGINT / NUMERIC | NUMBER(38,0) | Snowflake has one numeric type under several aliases. |
| BYTEA | BINARY | Direct equivalent. |
PostgreSQL to Snowflake: what actually catches people out
Syntax is the part a translator can fix. These are the differences that survive a clean conversion and show up later as wrong results rather than as errors.
Unquoted identifiers fold up, not down
This is the one that catches everybody. PostgreSQL lowercases unquoted identifiers; Snowflake uppercases them. A table created unquoted in Postgres as users is `users`; the same statement in Snowflake creates `USERS`. Code that then quotes "users" will not find it. Either quote consistently in both or never quote at all.
JSONB operators do not carry over
Postgres's ->, ->> and @> have no Snowflake equivalent. VARIANT columns use colon notation for paths and require explicit casts to get a typed value out — col:field::string rather than col->>'field'. Any query doing real JSON work needs rewriting by hand.
SELECT data->>'email' FROM users;SELECT data:email::string FROM users;Constraints are metadata, not enforcement
Snowflake accepts PRIMARY KEY, FOREIGN KEY and UNIQUE declarations and enforces none of them except NOT NULL. They exist for the optimiser and for documentation. Anything relying on the database to reject a duplicate has to move that check upstream.
No indexes — and you do not need them
There is nothing to create. Snowflake prunes micro-partitions using the clustering of the data itself, so the tuning lever is a cluster key on a large table, not an index. CREATE INDEX statements simply have no target.
What this converter will not do
Query Studio translates SQL syntax. Being honest about the boundary is more useful than claiming there isn’t one — and on PostgreSQL → Snowflake specifically, these are the three that matter most:
Performance characteristics
A converted query is correct, not fast. Index strategy, partitioning, distribution keys and statistics differ per engine, and a query that was well-tuned for the source is merely valid on the target. Run the Analyze and Optimize tabs on the output.
Vendor-specific extensions
PostGIS geometry, MySQL spatial functions, SQL Server's FOR XML and hierarchyid, BigQuery's nested/repeated model, Snowflake's time travel. Where there is no equivalent concept, there is no translation — only a redesign.
Stored procedures, functions and triggers
Procedural code — PL/pgSQL, T-SQL procedures, MySQL routines — is a different language in every engine, with different control flow, error handling, variable declaration and transaction semantics. Query Studio translates queries, not programs. These have to be ported by hand.
The full list of what a syntax translator cannot do is on the Query Studio page.
How to convert PostgreSQL to Snowflake
- Open the Query Studio editor and choose PostgreSQL as the “From” dialect.
- Choose Snowflake as the “To” dialect.
- Paste your PostgreSQL query and press Translate — copy the Snowflake result.
Try it with your own query
The editor is preloaded with PostgreSQL → Snowflake. You can also explain, format, validate and analyze the result.
Convert PostgreSQL to Snowflake now →Working with the data rather than the schema? Open a large CSV, JSON or Parquet file and query it with SQL — no upload, no row limit, and files far past what Excel will open.
PostgreSQL to Snowflake FAQ
Is this PostgreSQL to Snowflake converter free?
Yes — it's completely free with no account, no sign-up and no usage limits. Your query is processed to return the result and never stored.
Is the PostgreSQL to Snowflake conversion accurate?
Query Studio rewrites syntax deterministically using real SQL parsers, so it gives the same result every time — there is no AI involved and no variation between runs. It handles the differences listed above automatically. What it cannot do is anything semantic: stored procedures, triggers, vendor extensions and performance characteristics all need a human. Review complex, vendor-specific queries before running them in production.
What breaks when migrating from PostgreSQL to Snowflake?
The differences that most often cause problems on this pair: Unquoted identifiers fold up, not down; JSONB operators do not carry over; Constraints are metadata, not enforcement; No indexes — and you do not need them. Each is explained in full above, with before-and-after examples where seeing it is quicker than reading about it.
How do PostgreSQL data types map to Snowflake?
The full mapping table is above and covers 8 types. The ones that are not a straight rename: TEXT / VARCHAR(n) → VARCHAR, JSONB → VARIANT, INTEGER / BIGINT / NUMERIC → NUMBER(38,0). Note that Query Studio translates queries rather than schemas — the table is there to tell you what your CREATE TABLE statements need, not to rewrite them for you.
Does this PostgreSQL to Snowflake converter use AI?
No. Every result is computed by real SQL parsers and rule engines, which is what makes it free, instant, unlimited and identical on every run. Nothing is sent to a model, so there are no rate limits, no per-request cost to pass on, and no possibility of a confidently wrong answer that looks plausible.