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Data warehouse ⇄ CRM

Apache Hive to Apollo.io integration — real-time, two-way sync

Keep Apache Hive and Apollo.io 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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  • 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 Apollo.io

Sync Apollo.io 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. Accounts, People (database records), Sequences, Deals (Opportunities) from Apollo.io land in Apache Hive as live tables, updated within seconds, and columns computed in Apache Hive write back to fields in Apollo.io. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.

Common use cases

  • Land sequence enrollment status and outcomes in a warehouse for outbound performance reporting.
  • Deduplicate contacts across Apollo and the CRM by syncing on email as the match key.
  • Extract curated Hive tables into operational databases or SaaS tools so business teams use data locked in Hadoop.
  • Load records from CRMs and databases into partitioned Hive tables for long-term analytical storage.

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 Apollo.io are queryable in Apache Hive moments after they change, so dashboards stop lagging the reality they describe.

Scores and segments back on the record

Lead scores, churn risk, or usage segments computed in Apache Hive appear as fields in Apollo.io, where the people working accounts actually see them.

What you can sync between Apache Hive and Apollo.io

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 Apollo.io objects
Metastore Catalog The schema registry other engines (Spark, Presto, Impala) also read. Contacts People saved to your Apollo account, synced with emails, phone numbers, and enrichment fields.
Databases Metastore namespaces that scope tables and grants. Accounts Company records with firmographic attributes, matched to CRM accounts during sync.
Managed Tables Tables whose data lifecycle Hive controls, used as warehouse destinations. People (database records) Prospects from Apollo's global database, pulled into downstream systems once enriched or saved.
External Tables Tables over existing files in HDFS or object storage, read without moving data. Sequences Outreach cadences (emailer campaigns in the API); enrollment status is read to track which contacts are being worked.
Partitions Directory-mapped subsets (often by date) that bound incremental sync reads. Deals (Opportunities) Pipeline records that can be read and written to keep Apollo aligned with the CRM of record.
Views Logical views readable as modeled sources. Tasks and calls Rep activity records synced for activity reporting and coaching workflows.
What ships with Apache Hive ⇄ Apollo.io

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Hive or Apollo.io 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 Apollo.io record.

Observability

Monitoring

Track your Apache Hive ⇄ Apollo.io 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 Apollo.io.

How the Apache Hive and Apollo.io 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

Apollo.io

Integration surface
REST API
Authentication
API key (passed in request headers); master keys unlock account-wide endpoints
Change detection
Polling on updated-at timestamps; webhook callbacks exist only for delivering asynchronous enrichment results, not as a general change-event stream
Capabilities
read · write
Rate limits
Rate limits and enrichment credits vary by plan; bulk endpoints are throttled separately from single-record calls
How it works

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

    Choose tables

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

Apache Hive and Apollo.io 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
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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 Apollo.io.

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