HubSpot to Postgres integration for a queryable CRM replica
The HubSpot to Postgres integration from Adapters syncs contacts, companies, deals, and their associations from the HubSpot CRM API into your own Postgres tables on an incremental schedule, so product features and internal reporting query CRM data with plain SQL instead of paging the HubSpot API. Field mapping is no-code, so try it against sample records in the live demo.
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Last updated September 2026
What running HubSpot to Postgres by hand costs you
- HubSpot list views cannot join to your product usage or billing tables, so questions that span CRM and app data end up answered in a spreadsheet.
- The HubSpot API is paged and rate limited, so any live lookup from your own application is slow and fragile under load.
- Deals move stages constantly, and a one-time CSV export into Postgres is out of date before the next pipeline review.
The field mapping, out of the box
These cables are pre-wired when you pick the pair. Rewire any of them, or add your own, in the same visual data mapping tool you use for every adapter.
Input / HUBSPOT
Output / POSTGRES
Transforms included
Incremental loads use the hs_lastmodifieddate watermark so stage moves and property edits arrive on the next run; HubSpot returns every property as a string, so amounts cast to Postgres NUMERIC and epoch-millisecond timestamps become TIMESTAMPTZ in UTC, associations land in a bridge table so a contact can join to many deals, and writes upsert with ON CONFLICT on the HubSpot object id so a retry never double-inserts.
HubSpot to Postgres in depth
A Postgres replica of HubSpot is usually built so an application can query CRM data with plain SQL instead of paging an API under load. That goal changes the design: you care about freshness and correct types far more than about analytical scan speed. Read from HubSpot and PostgreSQL documentation on 20 August 2026.
Batch reads and a high-water mark, not a live API call
The reason to replicate at all is that the HubSpot API is paged and rate limited, so a live lookup from your own application is slow and fragile under load. Private apps get 100 requests per 10 seconds on Free and Starter and 190 on Professional and Enterprise, with daily account totals from 250,000 to 1,000,000. Read in batches of 100 records per call, filter on last modified date, and keep a high-water mark per object. Avoid the CRM Search API in any per-record loop: it is capped at 5 requests per second and at 10,000 results per query. See the HubSpot API rate limits guide.
Put custom properties in JSONB, not in 300 columns
HubSpot portals accumulate custom properties, and every one added by a marketer becomes a schema migration if your table is fully typed. The pattern that survives is a typed column for the handful of properties your application actually reads, plus a JSONB column holding the full property bag. Add a GIN index on the JSONB column if you filter on it. You keep type safety where it matters and absorb drift everywhere else, without a nightly load failing because somebody renamed a field.
Money is NUMERIC, never MONEY or float
Use NUMERIC(19,4) for deal amounts. The PostgreSQL MONEY type carries a locale-dependent fractional precision set by a server parameter, which makes it unsafe to move between environments, and floating point cannot represent decimal currency exactly. This is the same rule that applies coming from SQL Server, where MONEY maps to NUMERIC(19,4) rather than to PG MONEY. Amounts that are off by fractions of a cent are the hardest reconciliation bug to find because every individual row looks right.
TIMESTAMPTZ, and store UTC
HubSpot returns timestamps as epoch milliseconds in UTC. Land them in TIMESTAMPTZ so the zone travels with the value, rather than TIMESTAMP, which stores a naive local time and forces every consumer to remember an unwritten convention. Convert to a local date only at the point where a human definition of a day is applied, which is usually a report and not the replica.
Upsert with ON CONFLICT on the HubSpot object ID
Make the HubSpot object ID a unique constraint and write with INSERT ... ON CONFLICT (hubspot_id) DO UPDATE. That makes the load idempotent, so a job that runs twice after a retry produces the same table rather than duplicate rows. Add an updated_at column set by the loader, not by HubSpot, so you can tell the difference between a record HubSpot changed and a record your pipeline touched.
Associations are a separate table, and they matter
The relationship between a deal and its contacts is many-to-many, and flattening it into a single contact ID column on the deal loses data the moment a second contact is attached. Replicate associations into their own table keyed by both object IDs and the association type, with a composite primary key so re-running the sync is idempotent. This is the part most hand-built replicas skip, and it is the part that makes questions like which contacts touched closed-won deals answerable in SQL.
If you replicate onward with logical replication, know what it excludes
Teams often fan this Postgres replica out to a warehouse using logical replication. It requires wal_level = logical, with max_replication_slots at least the subscription count plus a table-sync reserve. It replicates tables only: not DDL, not sequence values, not large objects, and views or materialized views raise an error. PostgreSQL 18, released 25 September 2025, added idle_replication_slot_timeout, which is the fix for the classic failure where an inactive slot retains WAL until the disk fills. More in Postgres ETL tools.
Index for the queries the application makes, then stop
A CRM replica serving an application has a small, known query set: lookup by HubSpot ID, lookup by email, filter by owner, filter by stage. Index exactly those and resist the urge to index every column that appears in a WHERE clause once. Every index is write amplification on a table your sync rewrites continuously, and a replica that falls behind because of index maintenance is worse than one missing an index.
How it goes live
Three steps, minutes end to end, covered by flat data integration pricing from $49 a month.
STEP 01
Pick the pair
Connect HubSpot and Postgres with scoped credentials. About a minute each.
STEP 02
Confirm the mapping
The cables above are pre-wired. Adjust any field, preview the transform on sample records, done.
STEP 03
Schedule the sync
Hourly down to every minute, with retries, alerting, and a full log on every run.
HubSpot to Postgres sync: common questions
How do I connect HubSpot to Postgres?
Authorize the portal, choose the objects and properties you want, map them onto Postgres columns, and set a schedule. Adapters paginates the CRM API inside its rate limits and upserts on the HubSpot object id with ON CONFLICT, so the table holds current CRM state that an application or a BI tool can query directly.
Can I write HubSpot custom properties into Postgres?
Yes, and you should plan for them from the start. A working HubSpot portal accumulates dozens or hundreds of custom properties, and they are usually the ones the business actually reports on. Map them into typed columns where the type is stable, and keep the remainder in a JSONB column so a newly created property does not break the load.
Why sync HubSpot to Postgres instead of a warehouse?
Because the consumer is an application, not an analyst. If a product feature, an internal tool or a customer portal needs CRM context in the same database it already queries, Postgres is the right destination and a warehouse adds a network hop. If the consumer is a BI dashboard over years of history, a columnar warehouse is the better answer.
How do I handle deleted HubSpot records in Postgres?
Carry the archived flag through as a column and filter on it, rather than deleting rows locally. HubSpot archives records instead of hard-deleting them in most flows, and a sync that only sees active records has no way to tell you a deal disappeared. Soft state in the destination keeps history intact and makes the count reconcilable.
How does the HubSpot to Postgres sync work?
The HubSpot to Postgres integration from Adapters syncs contacts, companies, deals, and their associations from the HubSpot CRM API into your own Postgres tables on an incremental schedule, so product features and internal reporting query CRM data with plain SQL instead of paging the HubSpot API. Field mapping is no-code, so try it against sample records in the live demo.
Is there a prebuilt HubSpot connector for Postgres?
Yes. This HubSpot to Postgres connector ships prebuilt: the field mapping is wired the moment you pick the pair, transforms are included, and you can try it against sample records in the live demo. No code or engineering sprint required.
How much does the HubSpot Postgres integration cost?
Pricing is flat and monthly: Starter at $49, Growth at $149, Scale at $399. Every plan includes this pair, visual field mapping, and per-record logs. There are no per-task or per-row fees, so the bill stays the same as volume grows.
How often can Adapters sync HubSpot to Postgres?
Hourly on Starter, every 5 minutes on Growth, and down to every minute on Scale. Failed records retry automatically with backoff, and alerting plus a full per-record log come standard on every run.
Do I need to write code to connect HubSpot and Postgres?
No. Fields are auto-mapped the moment you pick the pair, and you can rewire any mapping visually before the first sync. Incremental loads use the hs_lastmodifieddate watermark so stage moves and property edits arrive on the next run; HubSpot returns every property as a string, so amounts cast to Postgres NUMERIC and epoch-millisecond timestamps become TIMESTAMPTZ in UTC, associations land in a bridge table so a contact can join to many deals, and writes upsert with ON CONFLICT on the HubSpot object id so a retry never double-inserts.
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HubSpot and Postgres, finally in agreement
Map the pair once and let it sync on schedule. Flat price from $49 a month, no per-task fees.
No credit card required.