Sequin
UnclaimedBuild integrations with APIs using SQL, treating them like a Postgres database.
Visit WebsiteFreemiumVisit Website
Tracked since2026
0 reviews trackedThe Bottom Line
Entry price
Free plan available, paid tiers above
Biggest pro
Simplifies complex API integrations using familiar SQL
Biggest con
Requires a Postgres database for integration
TL;DR - Sequin
- Syncs APIs to your Postgres database in real-time.
- Allows API interactions using standard SQL (SELECT, INSERT, UPDATE, DELETE).
- Simplifies integration development by abstracting API complexities like rate limits and pagination.
Pricing: Free plan available
Best for: Growing teams
What is Sequin?
Sequin provides a real-time, bidirectional sync between various APIs (like Salesforce, Airtable, Hubspot) and your PostgreSQL database. It allows developers to interact with these APIs using standard SQL queries (SELECT, INSERT, UPDATE, DELETE), effectively turning complex API interactions into simple database operations. This eliminates the need to deal with API documentation, query parameters, rate limits, and pagination, significantly simplifying integration development.
The product is designed for engineering teams looking to accelerate their development cycles and reduce the complexity of building and maintaining API integrations. By abstracting API complexities behind a familiar SQL interface, Sequin enables faster problem-solving, quicker deployment of new features, and reduces time spent debugging API-specific issues. It's particularly beneficial for those who are already proficient in SQL and database management, allowing them to leverage existing skills for API integration.
Available on: Web
Pros & Cons
Pros
- Simplifies complex API integrations using familiar SQL
- Accelerates development by reducing API-specific boilerplate code
- Improves performance with faster reads and optimized queries
- Provides a consistent error handling mechanism
- Leverages existing database knowledge and tools
Cons
- Requires a Postgres database for integration
- Shutdown announced for October 23, 2025
Preview
Key Features
Real-time bidirectional sync between APIs and PostgresInteract with APIs using standard SQL (SELECT, INSERT, UPDATE, DELETE)Automatic handling of API query parameters, rate limits, and paginationErrors returned in standard Postgres formatSupport for Postgres features like views, generated columns, and triggers100x faster reads compared to direct API callsData validation against the source API during mutationsDedicated sync workers for real-time updates
Pricing Plans
Free TrialPricing checked May 28, 2026
First 10K MAR
Free
10K → 100K MAR
$8.00 / 1K MAR
100K → 1M MAR
$2.00 / 1K MAR
1M → 10M MAR
$0.90 / 1K MAR
10M → 100M MAR
$0.34 / 1K MAR
100M → ∞ MAR
$0.08 / 1K MAR
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Sequin FAQ
How does Sequin handle errors during data mutations?
Sequin returns errors in a standard Postgres format, allowing for inline handling. This eliminates the need to search forums to decipher cryptic API responses.
Can I use SQL to create complex database objects with Sequin?
Yes, Sequin allows users to create views, generated columns, and triggers. You can also add PostgreSQL extensions and write functions to build your application logic.
What is the pricing model for Sequin and how are 'monthly active rows' calculated?
Sequin uses a usage-based pricing model, charging for 'monthly active rows' (MAR). MAR represents the number of distinct rows synced between your source and database in a billing period, counted once per month even if updated multiple times.
Does the initial synchronization of data contribute to the monthly active rows count?
No, backfills and complete re-syncs of all data to your database are not included in the calculation of monthly active rows.
What is the difference in real-time synchronization capabilities between the free and pro tiers?
On the pro tier, Sequin provides a dedicated, auto-scaling cluster of workers for real-time syncs, ensuring your database is only a couple of seconds behind the API. The free tier offers up to one dedicated sync worker, which may lead to lag at high data volumes.
Source: sequin.io