Skip to content
Database ⇄ Business productivity

Jdbc to Lusha integration — real-time data sync

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

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

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

Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Jdbc and Lusha

Mirror Lusha's data into Jdbc so your own code can read and write it like any other table, with changes flowing both ways in seconds.

Lusha is a read-only source: Stacksync reads its data in real time and delivers it into Jdbc, so Jdbc always reflects the current state of Lusha — without exports, scripts, or schedulers.

Engineers integrate with tools like Lusha through APIs, which means auth, pagination, rate limits, webhooks, and retry logic, all maintained forever and all different for every tool. Meanwhile the data would be trivial to use if it simply lived in Jdbc.

Stacksync mirrors Prospecting Results, Bulk Enrichment Requests, Person Profiles, Company Profiles from Lusha into Views, Columns, Primary keys & indexes, Schemas & catalogs in Jdbc and keeps both sides in sync in real time. Your services query the database directly, and inserts or updates your code makes flow back into Lusha, so the tool and the database never disagree.

Common use cases

  • 01 Append firmographic company data to account records before territory or scoring runs.
  • 02 Build prospecting lists from Lusha search results and sync them into the CRM as leads.
  • 03 Write records from a CRM, ERP, or another app back into database tables via SQL INSERT and UPDATE so the database stays current.
  • 04 Connect a niche or legacy RDBMS that has no dedicated Stacksync connector but ships a JDBC driver, using its JDBC URL to sync it two-way.

Common sync patterns

React to changes as they happen

Updates in Lusha arrive as row changes in Jdbc, so triggers, jobs, and services can respond in near real time.

One integration pattern for the whole stack

Every synced tool looks the same from the database, so each new integration is configuration, not a new codebase.

Read Lusha with a query

Records from Lusha are ordinary rows in Jdbc; join them, index them, and use them in application logic without touching the vendor API.

What you can sync between Jdbc and Lusha

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.

Jdbc objects Lusha objects How this pairing syncs
Columns Per-table fields with data types, nullability, and defaults; enumerated via DatabaseMetaData.getColumns to auto-generate and type-check field mappings. Phone Numbers Direct-dial and mobile numbers appended for outbound calling workflows. Columns is specific to Jdbc and Phone Numbers to Lusha — each maps to any object or custom field on the other side.
Primary keys & indexes Key and index definitions read via DatabaseMetaData; the primary key is required for reliable upserts, and indexes on the cursor column keep incremental polling fast. Prospecting Results Search-based lists of people and companies matching filters, used to seed lead lists. Primary keys & indexes is specific to Jdbc and Prospecting Results to Lusha — each maps to any object or custom field on the other side.
Schemas & catalogs Namespaces that group tables and views; the connector targets a schema/catalog and lists its objects from the JDBC metadata to build the sync. Bulk Enrichment Requests Batch lookups that enrich multiple records per request, used to backfill large contact lists rather than one-off calls. Schemas & catalogs is specific to Jdbc and Bulk Enrichment Requests to Lusha — each maps to any object or custom field on the other side.
Stored procedures & functions Server-side routines callable via JDBC CallableStatement; invoked for custom read or write logic when a table-level mapping is not enough. Person Profiles Contact-level enrichment results (work emails, phone numbers, title, company) returned per lookup. Stored procedures & functions is specific to Jdbc and Person Profiles to Lusha — each maps to any object or custom field on the other side.
Sequences Server-generated identity values; relevant when writing rows into tables whose keys are assigned by the database rather than the source system. Company Profiles Firmographic records (industry, size, location) appended to account or company rows. Sequences is specific to Jdbc and Company Profiles to Lusha — each maps to any object or custom field on the other side.
Tables The base relational tables in the target database; synced two-way as rows over SQL, with each table's primary key driving upserts and row-level updates. Email Addresses Work emails written into CRM contact fields during enrichment. Tables is specific to Jdbc and Email Addresses to Lusha — each maps to any object or custom field on the other side.

How changes propagate between Jdbc and Lusha

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.

Jdbc Lusha Interval-based propagation

DetectionStacksync polls Jdbc for changes on an incremental schedule, reading only records changed since the previous pass. No native change feed.

DeliveryLusha does not accept inbound record writes, so this direction carries requests rather than records: Lusha's output flows back as field updates on the originating Jdbc records.

Lusha Jdbc Interval-based propagation

DetectionStacksync polls Lusha for changes on an incremental schedule, reading only records changed since the previous pass. Data is fetched on demand per lookup, so syncs poll or trigger enrichment when source records change.

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

Rate-limit considerations

  • Jdbc: No SaaS-style request quota. Throughput is bounded by the target database's max connections and connection-pool size, plus the CPU and I/O it shares with production queries, so heavy syncs can contend with live workloads.
  • Lusha: Lookups consume credits and are subject to the platform's API rate limits.
What ships with Jdbc ⇄ Lusha

Connect Jdbc and Lusha for flexible, real-time data sync.

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

Real-time

Real-time sync

Changes in Jdbc or Lusha instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Jdbc or Lusha 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 Jdbc or Lusha record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Jdbc and Lusha.

How the Jdbc and Lusha connectors work

Jdbc

Integration surface
JDBC API (java.sql / javax.sql) executing SQL through a JDBC driver, typically a pure-Java Type 4 driver; reaches any relational database with a driver - PostgreSQL, MySQL, SQL Server, Oracle, IBM DB2, and others - via a JDBC URL such as jdbc:postgresql://host:5432/db.
Authentication
A database user's username and password supplied in the JDBC connection (DriverManager or a DataSource), typically over a TLS/SSL-encrypted connection. Some drivers add Kerberos, integrated Windows auth, or cloud IAM-token auth, but the available methods depend on the target database and its driver.
Change detection
No native change feed. Incremental sync polls a cursor column - an updated_at timestamp or an auto-incrementing key - to pull new and changed rows; detecting deletes needs soft-delete flags or database triggers writing to a shadow table. No webhooks.
Capabilities
read · write
Rate limits
No SaaS-style request quota. Throughput is bounded by the target database's max connections and connection-pool size, plus the CPU and I/O it shares with production queries, so heavy syncs can contend with live workloads.

Lusha

Integration surface
REST API
Authentication
API key
Change detection
Not event-driven; data is fetched on demand per lookup, so syncs poll or trigger enrichment when source records change
Capabilities
read
Rate limits
Lookups consume credits and are subject to the platform's API rate limits.
How it works

How to connect Jdbc to Lusha — 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 Jdbc and Lusha 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
    Jdbc connected
    Lusha connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Jdbc and Lusha 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 · Jdbc ⇄ Lusha
    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
    Jdbc Lusha
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Jdbc and Lusha 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.

Learn more about security
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

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 300 integrations available for Jdbc and Lusha.

Popular · 7 of 300
All Jdbc integrations All Lusha integrations Browse all integrations
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.

Book a demo Tour the platform on your own