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Data warehouse ⇄ ERP

Apache Hive to DEAR Inventory integration — real-time, two-way sync

Keep Apache Hive and DEAR Inventory 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

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Why teams connect Apache Hive and DEAR Inventory

Put DEAR Inventory's records in Apache Hive as live tables for reporting and analysis, without extract jobs, and write results back where DEAR Inventory can use them.

ERP data is some of the most asked-for data in the warehouse and some of the hardest to get: the record types are many, the APIs are strict, and extract jobs are brittle. Whether DEAR Inventory carries financials, operations, workforce data, or all three, the analysis belongs in Apache Hive next to everything else the company measures.

Stacksync syncs Customers, Suppliers, Stock adjustments and transfers, Assemblies / Production from DEAR Inventory into tables in Apache Hive continuously, managing API limits and schema drift along the way. The connection is bi-directional, so values computed in Apache Hive can be written back to fields in DEAR Inventory where that is useful.

Common use cases

  • Sync new date partitions incrementally instead of rescanning full tables.
  • Publish Hive aggregate tables to a faster serving database for dashboards.
  • Push sale orders from a storefront or CRM into DEAR for fulfillment without manual re-entry.
  • Land orders, costs, and inventory movements in a warehouse for margin and stock-turn reporting.

Where DEAR Inventory holds the books: finance reporting from live data

Financial records land in Apache Hive as they change, so period-end reporting queries current numbers rather than last night's extract.

Where DEAR Inventory is the HR system of record: workforce analytics

Worker and organization data syncs into Apache Hive for headcount, cost, and planning analysis alongside other company data.

Where DEAR Inventory runs operations: order and supply analysis

Operational records become queryable tables in Apache Hive, joinable with sales and finance data.

What you can sync between Apache Hive and DEAR Inventory

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 Hive objects DEAR Inventory objects
Partitions Directory-mapped subsets (often by date) that bound incremental sync reads. Products SKU records with pricing, suppliers, and bill-of-material links; the master data most syncs start from.
Views Logical views readable as modeled sources. Stock levels Per-location availability derived from inventory transactions; read-heavy in storefront syncs.
Materialized Views Precomputed results available in newer Hive versions for faster reads. Sale orders Customer orders through their pick/pack/ship lifecycle; synced with storefronts and CRMs.
ACID Tables ORC-backed transactional tables that support row-level insert, update, and delete. Purchase orders Supplier orders and receiving records synced with accounting and planning tools.
Metastore Catalog The schema registry other engines (Spark, Presto, Impala) also read. Customers Buyer records aligned with CRM and accounting counterparts.
Databases Metastore namespaces that scope tables and grants. Suppliers Vendor records referenced on purchase orders.
What ships with Apache Hive ⇄ DEAR Inventory

Connect Apache Hive and DEAR Inventory for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Hive–DEAR Inventory connection.

Real-time

Two-way sync

Changes in Apache Hive or DEAR Inventory instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Hive or DEAR Inventory 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 Apache Hive or DEAR Inventory record.

Observability

Monitoring

Track your Apache Hive ⇄ DEAR Inventory sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Apache Hive and DEAR Inventory.

How the Apache Hive and DEAR Inventory connectors work

Apache Hive

Integration surface
SQL (HiveQL) over JDBC/ODBC via HiveServer2 (Thrift)
Authentication
Deployment-dependent: Kerberos, LDAP, or username/password
Change detection
Polling on partition values or timestamp columns; no general-purpose change log for external consumers
Capabilities
read · write
Rate limits
No API quotas; query latency reflects the batch-oriented execution engine underneath

DEAR Inventory

Integration surface
REST API
Authentication
Account ID plus application key sent as request headers
Change detection
Polling with modified-since filters; webhook notifications for sale and purchase events are available on subscriptions that include the Automation module
Capabilities
read · write · webhooks
Rate limits
Subject to the platform's per-account API rate limits
How it works

How to connect Apache Hive to DEAR Inventory — 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 Apache Hive and DEAR Inventory 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
    Apache Hive connected
    DEAR Inventory connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Apache Hive and DEAR Inventory 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 · Apache Hive ⇄ DEAR Inventory
    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
    Apache Hive DEAR Inventory
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Apache Hive and DEAR Inventory integration FAQ

SECURITY

Security teams love 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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ISO 27001
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→ 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 386 integrations available for Apache Hive and DEAR Inventory.

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