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Database ⇄ Human resources

AWS Aurora PostgreSQL to Lever integration — real-time, two-way sync

Keep AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL and Lever

Put your workforce data where your apps can reach it: AWS Aurora PostgreSQL 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. AWS Aurora PostgreSQL is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: Postings, Requisitions, Offers, Users in Lever need to exist as queryable Columns, Primary keys and constraints, Views and materialized views, Foreign keys in AWS Aurora PostgreSQL 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 Columns, Primary keys and constraints, Views and materialized views, Foreign keys in AWS Aurora PostgreSQL with Postings, Requisitions, Offers, Users 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 Feed operational dashboards from a read replica while the writer handles sync traffic.
  • 02 Expose ERP records such as customers, orders, and invoices as Postgres tables the engineering team can query and update with plain SQL.
  • 03 Write enriched Sources, Tags, and Contact data back onto Opportunities from an outbound sourcing pipeline.
  • 04 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.

Common sync patterns

One directory of record

When a person record is added, changed, or deactivated in either system, the matching row in the other stays current, ending dual maintenance.

Reporting and analytics on current data

Postings, Requisitions, Offers, Users replicate into AWS Aurora PostgreSQL where they join operational tables, so headcount, roles, and status reports run on the live state without manual pulls.

Org and structure stay aligned

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

What you can sync between AWS Aurora PostgreSQL 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.

AWS Aurora PostgreSQL objects Lever objects How this pairing syncs
Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. Stages Pipeline stage definitions that Opportunities move through; read to model funnel state and stage transitions in a database. Columns is specific to AWS Aurora PostgreSQL and Stages to Lever — each maps to any object or custom field on the other side.
Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. Feedback Interview feedback and scorecard forms attached to Opportunities; created via POST /opportunities/:id/feedback and consolidated into a warehouse for interviewer analytics. Primary keys and constraints is specific to AWS Aurora PostgreSQL and Feedback to Lever — each maps to any object or custom field on the other side.
Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. Interviews Scheduled interview panel events with times and interviewers; read for scheduling reporting and time-to-hire metrics, and creatable via the panels endpoint. Views and materialized views is specific to AWS Aurora PostgreSQL and Interviews to Lever — each maps to any object or custom field on the other side.
Foreign keys Relationship metadata that syncs can translate into object references elsewhere. Notes and Contacts Free-text Notes on Opportunities plus the underlying Contact (person) that dedupes multiple Opportunities; notes are posted via POST /opportunities/:id/notes and contact-level tags, sources, and links can be added back for attribution. Foreign keys is specific to AWS Aurora PostgreSQL and Notes and Contacts to Lever — each maps to any object or custom field on the other side.
Replication slots and publications The logical replication objects that power log-based CDC. 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. Replication slots and publications is specific to AWS Aurora PostgreSQL and Opportunities to Lever — each maps to any object or custom field on the other side.
Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. 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. Databases and schemas is specific to AWS Aurora PostgreSQL and Postings to Lever — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora PostgreSQL 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.

AWS Aurora PostgreSQL Lever Sub-second propagation

DetectionChanges in AWS Aurora PostgreSQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback.

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

Lever AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • 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 AWS Aurora PostgreSQL ⇄ Lever

Connect AWS Aurora PostgreSQL and Lever for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL or Lever record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between AWS Aurora PostgreSQL and Lever.

How the AWS Aurora PostgreSQL and Lever connectors work

AWS Aurora PostgreSQL

Integration surface
SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback
Capabilities
read · write · CDC

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 AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL 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
    AWS Aurora PostgreSQL connected
    Lever connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora PostgreSQL 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 · AWS Aurora PostgreSQL ⇄ 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
    AWS Aurora PostgreSQL Lever
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS Aurora PostgreSQL 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 452 integrations available for AWS Aurora PostgreSQL and Lever.

Popular · 7 of 452
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