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Data warehouse ⇄ CRM

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

Keep Apache Hive and Close 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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Migrated from Mulesoft
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Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Apache Hive and Close

Sync Close into Apache Hive continuously and push warehouse results back onto CRM records, one two-way connection instead of two pipelines.

The CRM feeds the warehouse and the warehouse should feed the CRM: relationship data flows one way, and computed scores, segments, and customer context flow back. Most teams build the first half as a batch pipeline and never quite get to the second.

Stacksync does both with one connection. Custom Activities, Custom Fields, Users, Smart Views from Close land in Apache Hive as live tables, updated within seconds, and columns computed in Apache Hive write back to fields in Close. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.

Common use cases

  • Write product usage or firmographic data from an internal database onto Close lead custom fields to prioritize follow-up.
  • Sync Close leads and opportunities into Postgres or a warehouse for pipeline reporting outside Close's built-in reports.
  • Bridge a legacy Hadoop warehouse to a cloud warehouse during migration by syncing tables continuously.
  • Extract curated Hive tables into operational databases or SaaS tools so business teams use data locked in Hadoop.

A single customer view

Join Close's relationship data with billing, product, and support data in Apache Hive to build the customer picture the CRM alone cannot hold.

Cleanup that sticks

Deduplication and normalization done in Apache Hive can be written back, so warehouse-side cleanup actually fixes the CRM.

CRM analytics on live data

Accounts, contacts, and activity from Close are queryable in Apache Hive moments after they change, so dashboards stop lagging the reality they describe.

What you can sync between Apache Hive and Close

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 Close objects
Partitions Directory-mapped subsets (often by date) that bound incremental sync reads. Custom Fields Org-specific fields on leads, contacts, and opportunities; addressed by stable field ids in syncs.
Views Logical views readable as modeled sources. Users Sales reps referenced as owners on leads, opportunities, and activities.
Materialized Views Precomputed results available in newer Hive versions for faster reads. Smart Views Saved lead searches that can scope which records a segment-based sync pulls.
ACID Tables ORC-backed transactional tables that support row-level insert, update, and delete. Leads The top-level record in Close; represents a company and holds its contacts, opportunities, and activity history.
Metastore Catalog The schema registry other engines (Spark, Presto, Impala) also read. Contacts People nested under a lead, with emails and phone numbers used for outreach syncs.
Databases Metastore namespaces that scope tables and grants. Opportunities Deal records with value, confidence, and status; commonly synced to reporting and billing systems.
What ships with Apache Hive ⇄ Close

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Hive or Close 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 Close record.

Observability

Monitoring

Track your Apache Hive ⇄ Close 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 Close.

How the Apache Hive and Close 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

Close

Integration surface
REST API
Authentication
API key (sent via HTTP Basic auth)
Change detection
Webhook subscriptions for record events, with polling on date_updated fields for backfills
Capabilities
read · write · webhooks
Rate limits
Subject to per-endpoint rate limits communicated in response headers
How it works

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

    Choose tables

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

Apache Hive and Close 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.

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 386 integrations available for Apache Hive and Close.

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