Two-way sync
Changes in Apache Hive or Gong instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Hive and Gong in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
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. Calls, Transcripts, Users, Interaction Stats (Activity) from Gong land in Apache Hive as live tables, updated within seconds, and columns computed in Apache Hive write back to fields in Gong. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.
Lead scores, churn risk, or usage segments computed in Apache Hive appear as fields in Gong, where the people working accounts actually see them.
Join Gong's relationship data with billing, product, and support data in Apache Hive to build the customer picture the CRM alone cannot hold.
Deduplication and normalization done in Apache Hive can be written back, so warehouse-side cleanup actually fixes the CRM.
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 | Gong objects | How this pairing syncs | |
|---|---|---|---|
| External Tables Tables over existing files in HDFS or object storage, read without moving data. | CRM Objects Accounts, opportunities, stages, and users uploaded into Gong through the CRM integration API so CRM context appears alongside conversations. Write (upload) path. | External Tables is specific to Apache Hive and CRM Objects to Gong — each maps to any object or custom field on the other side. | |
| Partitions Directory-mapped subsets (often by date) that bound incremental sync reads. | Library Call-library folders and folder content (curated calls and snippets) read via GET /v2/library/folders and /v2/library/folder-content. Read-only. | Partitions is specific to Apache Hive and Library to Gong — each maps to any object or custom field on the other side. | |
| Views Logical views readable as modeled sources. | Data Privacy (Erasure) GDPR/CCPA deletion handled by POST /v2/data-privacy/erase-data-for-email, with data-for-email lookups on the read side; a write path used for compliance deletions. | Views is specific to Apache Hive and Data Privacy (Erasure) to Gong — each maps to any object or custom field on the other side. | |
| Materialized Views Precomputed results available in newer Hive versions for faster reads. | Calls Retrieved via POST /v2/calls/extensive with participants, topics, trackers, scorecards, and media URLs, filtered by fromDateTime/toDateTime; external recordings are also imported via POST /v2/calls with media uploaded via PUT /v2/calls/{id}/media. Read and write. | Materialized Views is specific to Apache Hive and Calls to Gong — each maps to any object or custom field on the other side. | |
| ACID Tables ORC-backed transactional tables that support row-level insert, update, and delete. | Transcripts Speaker-attributed, timestamped sentences retrieved via POST /v2/calls/transcript for one or more callIds; available only after asynchronous processing completes. Read-only. | ACID Tables is specific to Apache Hive and Transcripts to Gong — each maps to any object or custom field on the other side. | |
| Metastore Catalog The schema registry other engines (Spark, Presto, Impala) also read. | Users Gong users and team members with roles, titles, email, and settings, read via GET /v2/users to map call owners and participants to CRM and warehouse identities. Read-only. | Metastore Catalog is specific to Apache Hive and Users to Gong — 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 Hive for changes on an incremental schedule, reading only records changed since the previous pass. Polling on partition values or timestamp columns.
DeliveryEach detected change is written to Gong through its API, with automatic retries and rate-limit backoff.
DetectionStacksync polls Gong for changes on an incremental schedule, reading only records changed since the previous pass. Polling POST /v2/calls/extensive on fromDateTime/toDateTime.
DeliveryEach detected change is applied to Apache Hive 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 Hive–Gong connection.
Changes in Apache Hive or Gong instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Hive or Gong 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 Hive or Gong record.
Track your Apache Hive ⇄ Gong sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Hive and Gong.
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 Hive and Gong 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 Hive and Gong 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 Hive and Gong: authenticate both systems, choose the objects to sync (such as Apache Hive's External Tables and Partitions), map fields visually, and changes propagate both ways in milliseconds — no code required.
Apache Hive: SQL (HiveQL) over JDBC/ODBC via HiveServer2 (Thrift). Authentication: Deployment-dependent: Kerberos, LDAP, or username/password. Gong: REST API on api.gong.io/v2 - retrieval endpoints (calls, transcript, users, stats, settings, library, logs) plus write endpoints for importing calls, uploading CRM data, and data-privacy erasure. Authentication: Basic authorization header combining an Access Key and Access Key Secret (created by a Gong technical admin, base64-encoded as key:secret); OAuth 2.0 Bearer tokens are supported for marketplace apps. Stacksync manages authentication, retries, and rate limits on both sides.
Gong: Writes follow a system-of-engagement pattern - importing external call recordings (POST /v2/calls plus media upload), uploading CRM objects for context, and data-privacy erasure - so Gong is not a general write target for arbitrary business records. Apache Hive: Row-level ACID transactions are supported on ORC-backed transactional tables in Hive 3, but classic tables remain append-oriented. Stacksync's field mapping accounts for these differences between Apache Hive and Gong 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 Hive and Gong records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Apache Hive and Gong connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Apache Hive–Gong integration in-house.
Yes — Stacksync ships production-grade connectors for both Apache Hive and Gong. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 463 integrations available for Apache Hive and Gong.