Two-way sync
Changes in Apache Pinot or Lever instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Pinot 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.
Workforce data is some of the most requested data in the warehouse and some of the most awkward to move: the record types are many, the fields carry sensitive personal information, the APIs are strict, and hand-built extract jobs go stale or break quietly. Whether Lever is the system of record for employees and payroll, for candidates and applications, or for learners and course completions, the reporting belongs in Apache Pinot next to everything else the company measures.
Stacksync syncs Users, Stages, Feedback, Interviews from Lever into tables in Apache Pinot continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in Apache Pinot, such as headcount rollups, cost allocations, or attrition risk flags, can be written back to fields in Lever where the HR team acts on them. You configure which records and fields cross over, and in which direction, instead of maintaining pipeline code.
A continuously synced copy in Apache Pinot gives you a durable, queryable record of how Lever's records change over time, for headcount planning and audit questions.
Segments, rollups, or risk flags computed in Apache Pinot sync back onto the matching records in Lever, where the HR team sees them in the system they already use.
People and organization records from Lever arrive in Apache Pinot as queryable tables, current within seconds instead of a day behind, replacing hand-built extract jobs.
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.
| Apache Pinot objects | Lever objects | How this pairing syncs | |
|---|---|---|---|
| Tables The queryable unit, defined as offline, real-time, or hybrid; the main read target. | Feedback Interview feedback and scorecard forms attached to Opportunities; created via POST /opportunities/:id/feedback and consolidated into a warehouse for interviewer analytics. | Tables is specific to Apache Pinot and Feedback to Lever — each maps to any object or custom field on the other side. | |
| Schemas Column definitions (dimensions, metrics, time columns) mapped during integration setup. | Interviews Scheduled interview panel events with times and interviewers; read for scheduling reporting and time-to-hire metrics, and creatable via the panels endpoint. | Schemas is specific to Apache Pinot and Interviews to Lever — each maps to any object or custom field on the other side. | |
| Segments Immutable data files that batch ingestion uploads and the cluster serves. | 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. | Segments is specific to Apache Pinot and Notes and Contacts to Lever — each maps to any object or custom field on the other side. | |
| Real-time Tables Tables fed continuously from streams like Kafka, including upsert-enabled tables. | 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. | Real-time Tables is specific to Apache Pinot and Opportunities to Lever — each maps to any object or custom field on the other side. | |
| Offline Tables Batch-loaded tables merged with real-time data at query time. | 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. | Offline Tables is specific to Apache Pinot and Postings to Lever — each maps to any object or custom field on the other side. | |
| Indexes Inverted, range, and star-tree indexes that determine which sync queries run at low latency. | 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. | Indexes is specific to Apache Pinot and Requisitions to Lever — each maps to any object or custom field on the other side. |
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.
DetectionStacksync polls Apache Pinot for changes on an incremental schedule, reading only records changed since the previous pass. Data enters Pinot via streaming ingestion or segment upload, not row-level writes.
DeliveryEach detected change is written to Lever through its API, with automatic retries and rate-limit backoff.
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 Apache Pinot as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Pinot–Lever connection.
Changes in Apache Pinot or Lever instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Pinot or Lever data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Apache Pinot or Lever record.
Track your Apache Pinot ⇄ Lever sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Pinot and Lever.
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.
Authenticate Apache Pinot 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.
Pick the Apache Pinot 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Apache Pinot and Lever: authenticate both systems, choose the objects to sync (such as Apache Pinot's Tables and Schemas), map fields visually, and changes propagate both ways in milliseconds — no code required.
Common patterns for Apache Pinot and Lever: Queryable history for planning and audit; Write-back of computed values; HR data in the warehouse, minus the pipeline. A continuously synced copy in Apache Pinot gives you a durable, queryable record of how Lever's records change over time, for headcount planning and audit questions.
Apache Pinot: REST API (SQL queries via the broker; administration via the controller); JDBC client available. Authentication: Deployment-dependent: HTTP basic authentication or token-based auth where enabled. Lever: 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). Stacksync manages authentication, retries, and rate limits on both sides.
Apache Pinot: Data is stored in immutable segments; batch writes happen by building and uploading segments rather than issuing row inserts. Lever: The /candidates endpoint is deprecated; the current model is Opportunities, where one person (Contact) can hold multiple Opportunities across postings, so deduplication keys on the Contact. Stacksync's field mapping accounts for these differences between Apache Pinot and Lever without custom code.
Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Apache Pinot and Lever records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Apache Pinot and Lever connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Apache Pinot–Lever integration in-house.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
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Every pair below is a real-time, two-way sync. Search all 437 integrations available for Apache Pinot and Lever.