Real-time sync
Changes in BetterContact or Cloudera Data Platform instantly reflect in both systems. No stale data, no manual imports.
Keep BetterContact and Cloudera Data Platform in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
BetterContact is a read-only source: Stacksync reads its data in real time and delivers it into Cloudera Data Platform, so Cloudera Data Platform always reflects the current state of BetterContact — without exports, scripts, or schedulers.
Whatever BetterContact is used for, it accumulates data the rest of the company wants to analyze, and that data usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay for it.
A continuously synced copy in Cloudera Data Platform preserves a queryable record even as data ages out of BetterContact or gets changed inside it.
Records and events from BetterContact land in Cloudera Data Platform as queryable tables, current within seconds and ready to join with the rest of the warehouse.
Combine BetterContact's data with data from every other synced system to answer questions no single tool can.
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.
| BetterContact objects | Cloudera Data Platform objects | How this pairing syncs | |
|---|---|---|---|
| Lead Finder Search Prospect discovery by people and company filters, returning enriched lead profiles. | Kudu tables Storage engine tables that support row-level inserts, updates, and deletes. | Lead Finder Search is specific to BetterContact and Kudu tables to Cloudera Data Platform — each maps to any object or custom field on the other side. | |
| Enrichment Request Batch or single submissions of up to 100 contacts per request for waterfall enrichment. | Iceberg tables Open table format tables in newer CDP versions, with snapshot metadata usable for incremental reads. | Enrichment Request is specific to BetterContact and Iceberg tables to Cloudera Data Platform — each maps to any object or custom field on the other side. | |
| Enriched Contact Verified work emails and mobile numbers with job title, LinkedIn profile, location, and skills. | Views SQL views that can present curated, sync-ready projections of raw lake data. | Enriched Contact is specific to BetterContact and Views to Cloudera Data Platform — each maps to any object or custom field on the other side. | |
| Company Company data returned with each contact: name, domain, HQ location, industry, employee count. | Partitions Table partitions (often by date) that incremental extraction jobs use to scope reads. | Company is specific to BetterContact and Partitions to Cloudera Data Platform — 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.
DetectionBetterContact notifies Stacksync of record changes through webhook events. Job-based delivery — enrichment results arrive by webhook push or polling of the results endpoint.
DeliveryEach detected change is applied to Cloudera Data Platform as a row-level write, with types converted between the two schemas.
DetectionStacksync polls Cloudera Data Platform for changes on an incremental schedule, reading only records changed since the previous pass. Polling via SQL on timestamp or partition columns.
DeliveryBetterContact does not accept inbound record writes, so this direction carries requests rather than records: BetterContact's output flows back as field updates on the originating Cloudera Data Platform records.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every BetterContact–Cloudera Data Platform connection.
Changes in BetterContact or Cloudera Data Platform instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever BetterContact or Cloudera Data Platform data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single BetterContact or Cloudera Data Platform record.
Track your BetterContact ⇄ Cloudera Data Platform sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between BetterContact and Cloudera Data Platform.
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 BetterContact and Cloudera Data Platform 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 BetterContact and Cloudera Data Platform 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 integration between BetterContact and Cloudera Data Platform — BetterContact is a read-only source, so data flows from it into the other system: authenticate both systems, choose the objects to sync, map fields visually, and changes propagate in milliseconds — no code required.
Yes — Stacksync ships production-grade connectors for both BetterContact and Cloudera Data Platform. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on BetterContact: Job-based delivery — enrichment results arrive by webhook push or polling of the results endpoint; there is no persistent record store to watch. On Cloudera Data Platform: Polling via SQL on timestamp or partition columns; no consumer-facing change feed. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the BetterContact side: Enriched Contact, Company, Lead Finder Search, Enrichment Request, plus custom fields where BetterContact exposes them. On the Cloudera Data Platform side: Object store / HDFS files, Databases, Hive tables, Impala tables. Stacksync auto-detects both schemas and converts types between the two systems.
BetterContact is a read-only source, so this integration runs one-way: Stacksync reads from BetterContact in real time and delivers into Cloudera Data Platform. Field mapping and monitoring work the same as for two-way pairs.
Common patterns for BetterContact and Cloudera Data Platform: History that outlives the tool; Analytics on BetterContact's data; Cross-tool reporting. A continuously synced copy in Cloudera Data Platform preserves a queryable record even as data ages out of BetterContact or gets changed inside 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 390 integrations available for BetterContact and Cloudera Data Platform.