Real-time
Two-way sync
Changes in Elasticsearch or Greenplum instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Data warehouse
Elasticsearch to Greenplum integration — real-time, two-way sync
Keep Elasticsearch and Greenplum 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
Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Elasticsearch and Greenplum
Connect Elasticsearch and Greenplum with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.
Operational databases and analytical warehouses want the same data at different moments. Analysts want Elasticsearch's rows in Greenplum, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in Elasticsearch where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Elasticsearch sync into Greenplum in real time, and result tables in Greenplum sync back into Elasticsearch, with schema and type mapping between the two systems handled for you.
Common use cases
- 01 Consolidate data from multiple source systems into partitioned Greenplum fact tables.
- 02 Load operational data from CRMs, ERPs, and production databases into Greenplum for MPP analytics.
- 03 Feed enriched customer records into an index used for vector or hybrid search in AI applications.
- 04 Sync CRM accounts and contacts into an Elasticsearch index to power internal search across customer records.
Common sync patterns
Offload heavy reads
Point analytical queries at the synced copy in Greenplum and keep Elasticsearch focused on its operational workload.
Operational data in the warehouse, minus the pipeline
Rows from Elasticsearch land in Greenplum as they change, replacing hand-built CDC and batch extract jobs.
Serve warehouse results at database speed
Aggregates or model outputs computed in Greenplum sync into Elasticsearch, where whatever reads from that database gets them without querying the warehouse.
What you can sync between Elasticsearch and Greenplum
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.
| Elasticsearch objects | Greenplum objects | How this pairing syncs | |
|---|---|---|---|
| Data streams Append-only targets for time-series or event data pushed from source systems. | External tables Reference external files for bulk load paths alongside row-level syncs. | Data streams is specific to Elasticsearch and External tables to Greenplum — each maps to any object or custom field on the other side. | |
| Ingest pipelines Server-side transforms applied to documents as a sync writes them. | Rows Read and written by key; distribution keys determine where rows live. | Ingest pipelines is specific to Elasticsearch and Rows to Greenplum — each maps to any object or custom field on the other side. | |
| Index templates Reusable settings and mappings applied automatically to new indices a sync creates. | Databases Top-level containers that scope a sync connection. | Index templates is specific to Elasticsearch and Databases to Greenplum — each maps to any object or custom field on the other side. | |
| Indices Target containers for synced records; each holds a table-like collection of JSON documents. | Schemas Namespace tables and control which objects a sync can see. | Indices is specific to Elasticsearch and Schemas to Greenplum — each maps to any object or custom field on the other side. | |
| Documents The unit of sync; JSON records created, updated, and deleted by _id. | Tables Heap or append-optimized tables mapped directly to sync targets. | Documents is specific to Elasticsearch and Tables to Greenplum — each maps to any object or custom field on the other side. | |
| Index mappings Field type definitions that determine how synced fields are indexed and queried. | Partitions Large tables are commonly partitioned by date, which shapes incremental reads. | Index mappings is specific to Elasticsearch and Partitions to Greenplum — each maps to any object or custom field on the other side. |
How changes propagate between Elasticsearch and Greenplum
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.
Elasticsearch Greenplum Interval-based propagation
DetectionStacksync polls Elasticsearch for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp or sequence fields.
DeliveryEach detected change is applied to Greenplum as a row-level write, with types converted between the two schemas.
Greenplum Elasticsearch Interval-based propagation
DetectionStacksync polls Greenplum for changes on an incremental schedule, reading only records changed since the previous pass. Polling with timestamp or key-based cursors.
DeliveryEach detected change is written to Elasticsearch through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- Elasticsearch: No fixed request quota; throughput is bounded by cluster sizing, thread pools, and bulk queue capacity.
- Greenplum: Bounded by cluster resources and concurrency settings rather than an API quota.
What ships with Elasticsearch ⇄ Greenplum
Connect Elasticsearch and Greenplum for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Elasticsearch–Greenplum connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Elasticsearch or Greenplum 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 Elasticsearch or Greenplum record.
Observability
Monitoring
Track your Elasticsearch ⇄ Greenplum sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Elasticsearch and Greenplum.
How the Elasticsearch and Greenplum connectors work
Elasticsearch
- Integration surface
- REST API (JSON over HTTP)
- Authentication
- API keys or basic authentication; Elastic Cloud also issues service account tokens
- Change detection
- Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks
- Capabilities
- read · write
- Rate limits
- No fixed request quota; throughput is bounded by cluster sizing, thread pools, and bulk queue capacity
Greenplum
- Integration surface
- PostgreSQL wire protocol (libpq), plus JDBC/ODBC drivers
- Authentication
- Database credentials
- Change detection
- Polling with timestamp or key-based cursors; Greenplum does not expose logical-decoding CDC
- Capabilities
- read · write
- Rate limits
- Bounded by cluster resources and concurrency settings rather than an API quota.
How it works
How to connect Elasticsearch to Greenplum — 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.
- 01
Connect your apps
Authenticate Elasticsearch and Greenplum with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Elasticsearch
connected
Greenplum
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Elasticsearch and Greenplum 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.
objects · Elasticsearch ⇄ GreenplumCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Elasticsearch GreenplumCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Elasticsearch and Greenplum integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Elasticsearch and Greenplum: authenticate both systems, choose the objects to sync (such as Elasticsearch's Data streams and Ingest pipelines), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Elasticsearch and Greenplum connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Elasticsearch–Greenplum integration in-house.
-
Yes — Stacksync ships production-grade connectors for both Elasticsearch and Greenplum. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
-
Change detection on Elasticsearch: Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks. On Greenplum: Polling with timestamp or key-based cursors; Greenplum does not expose logical-decoding CDC. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
-
On the Greenplum side: Tables, Partitions, Views, External tables, plus custom fields where Greenplum exposes them. On the Elasticsearch side: Ingest pipelines, Index templates, Indices, Documents. Stacksync auto-detects both schemas and converts types between the two systems.
-
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
SECURITY
Security teams trust 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.
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 452 integrations available for Elasticsearch and Greenplum.
Popular · 5 of 452
-
Elasticsearch ⇄ AWS S3 -
Elasticsearch ⇄ Amazon Redshift -
Elasticsearch ⇄ Apache Doris -
Greenplum ⇄ Neo4j -
Greenplum ⇄ Oracle DB
No integrations match .
