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Database ⇄ Human resources

DuckDB to Lever integration — real-time, two-way sync

Keep DuckDB and Lever in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect DuckDB and Lever

Put your workforce data where your apps can reach it: DuckDB and Lever share the same people, positions, and org structure in real time.

Lever is the system of record for the people side of the business — employees, candidates, roles, and the org structure around them. DuckDB is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: Interviews, Notes and Contacts, Opportunities, Postings in Lever need to exist as queryable Schemas, Tables, Views, External files (Parquet/CSV/JSON) in DuckDB before an app can act on them. When that bridge is a nightly export or a hand-run CSV, every downstream system spends the day working from a roster that has already moved on.

Stacksync syncs Schemas, Tables, Views, External files (Parquet/CSV/JSON) in DuckDB with Interviews, Notes and Contacts, Opportunities, Postings in Lever field by field, in real time. You decide which system owns which fields — Lever typically owns identity and org attributes, while operational or computed values can flow back the other way — and Stacksync keeps every copy consistent, matching records on a stable key and resolving conflicts by rules you set.

The result is one live picture of the workforce on both sides: HR keeps its source of truth, and the database keeps a current mirror that internal apps, reports, and access controls can trust without a batch window in between.

Common use cases

  • 01 Use DuckDB as a transform step: read synced Parquet exports, aggregate with SQL, and write results back to an operational database.
  • 02 Sync SaaS data to Parquet on object storage and query it with DuckDB without standing up a warehouse.
  • 03 Two-way sync Opportunities and their Stages between Lever and a Postgres database so recruiting ops and analysts query the pipeline in SQL while recruiters keep working in Lever.
  • 04 Push Postings and Requisitions into an HRIS or warehouse to reconcile approved headcount against open roles.

Common sync patterns

Org and structure stay aligned

Groups, departments, managers, and reporting lines from Lever stay consistent in DuckDB, so hierarchy-driven logic and permissions don't drift.

Computed and operational fields flow back

Values assembled or corrected in DuckDB write onto the matching record in Lever where those fields are writable, keeping the people system enriched.

Mirror people records into the database

Records maintained in Lever land as queryable Schemas, Tables, Views, External files (Parquet/CSV/JSON) in DuckDB, so internal apps and dashboards read live data instead of a periodic export.

What you can sync between DuckDB and Lever

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

DuckDB objects Lever objects How this pairing syncs
Schemas Namespaces within a database used to organize tables in sync outputs. Opportunities The core pipeline record for a candidate applying to a role; replaced the deprecated Candidates endpoint. Created via POST /opportunities and updated (stage, archive, links, tags, sources, files) through the API, and synced two-way with a database or HRIS. Schemas is specific to DuckDB and Opportunities to Lever — each maps to any object or custom field on the other side.
Tables Columnar tables created via SQL; the destination for materialized sync data. Postings Job posting records with categories, apply URLs, workplace type, and requisition codes. Can be created via POST /postings and read into a warehouse for open-role reporting. Tables is specific to DuckDB and Postings to Lever — each maps to any object or custom field on the other side.
Views SQL views used to shape or filter data for downstream consumers. Requisitions Headcount/requisition records with custom requisition fields, tied to Postings; read via GET /requisitions and synced to an HRIS to reconcile approved headcount against open roles. Views is specific to DuckDB and Requisitions to Lever — each maps to any object or custom field on the other side.
External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. Offers Offer records attached to an Opportunity with status and offer-form fields; exposed read-only through GET /opportunities/:id/offers, so they sync outbound to an HRIS or onboarding system when a candidate reaches the offer stage. External files (Parquet/CSV/JSON) is specific to DuckDB and Offers to Lever — each maps to any object or custom field on the other side.
Attached databases Additional database files or external systems attached into one session for cross-source queries. Users Lever team members (recruiters, hiring managers) with configurable roles; can be created via POST /users, deactivated, and reactivated through the API. Attached databases is specific to DuckDB and Users to Lever — each maps to any object or custom field on the other side.
Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. Stages Pipeline stage definitions that Opportunities move through; read to model funnel state and stage transitions in a database. Database files is specific to DuckDB and Stages to Lever — each maps to any object or custom field on the other side.

How changes propagate between DuckDB and Lever

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

DuckDB Lever Interval-based propagation

DetectionStacksync polls DuckDB for changes on an incremental schedule, reading only records changed since the previous pass. Polling or full re-reads.

DeliveryEach detected change is written to Lever through its API, with automatic retries and rate-limit backoff.

Lever DuckDB Sub-second propagation

DetectionLever notifies Stacksync of record changes through webhook events. Webhooks for candidate and application lifecycle events (applicationCreated, candidateStageChange, candidateArchiveStateChange, candidateHired,.

DeliveryEach detected change is applied to DuckDB as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • DuckDB: No API rate limits; throughput is bounded by local compute and I/O.
  • Lever: 10 requests/second per API key with a token-bucket burst to ~20/s; POSTs that create candidates/applications are throttled to roughly 2/second. Sustained overage returns 429 with Retry-After. List endpoints are cursor-paginated at up to 100 records per page.
What ships with DuckDB ⇄ Lever

Connect DuckDB and Lever for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every DuckDB–Lever connection.

Real-time

Two-way sync

Changes in DuckDB or Lever instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever DuckDB or Lever data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single DuckDB or Lever record.

Observability

Monitoring

Track your DuckDB ⇄ Lever sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between DuckDB and Lever.

How the DuckDB and Lever connectors work

DuckDB

Integration surface
In-process SQL engine via client libraries (Python, Node.js, JDBC, CLI); no server or network API by default
Authentication
None built in; access control is file-system level (MotherDuck adds token auth for its hosted service)
Change detection
Polling or full re-reads; no change feed or transaction log API
Capabilities
read · write
Rate limits
No API rate limits; throughput is bounded by local compute and I/O

Lever

Integration surface
REST Data API (api.lever.co/v1)
Authentication
API key over HTTP Basic auth (key as username, blank password) for internal integrations, or OAuth 2.0 with 1-hour access tokens for partner integrations (auth.lever.co)
Change detection
Webhooks for candidate and application lifecycle events (applicationCreated, candidateStageChange, candidateArchiveStateChange, candidateHired, interview created/updated/deleted), plus incremental polling via created_at and updated_at range filters on Opportunities
Capabilities
read · write · webhooks
Rate limits
10 requests/second per API key with a token-bucket burst to ~20/s; POSTs that create candidates/applications are throttled to roughly 2/second. Sustained overage returns 429 with Retry-After. List endpoints are cursor-paginated at up to 100 records per page.
Lever setup guide
How it works

How to connect DuckDB to Lever — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate DuckDB and Lever with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    DuckDB connected
    Lever connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the DuckDB and Lever objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · DuckDB ⇄ Lever
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    DuckDB Lever
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

DuckDB and Lever integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

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SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 448 integrations available for DuckDB and Lever.

Popular · 7 of 448
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