Two-way sync
Changes in Greenplum or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.
Keep Greenplum and TimescaleDB in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Operational databases and analytical warehouses want the same data at different moments. Analysts want TimescaleDB'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 TimescaleDB where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in TimescaleDB sync into Greenplum in real time, and result tables in Greenplum sync back into TimescaleDB, with schema and type mapping between the two systems handled for you.
Aggregates or model outputs computed in Greenplum sync into TimescaleDB, where whatever reads from that database gets them without querying the warehouse.
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Point analytical queries at the synced copy in Greenplum and keep TimescaleDB focused on its operational workload.
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.
| Greenplum objects | TimescaleDB objects | |
|---|---|---|
| Partitions Large tables are commonly partitioned by date, which shapes incremental reads. | Schemas Postgres namespaces used to separate synced datasets by team or environment. | |
| Views Read-only projections used to shape data before syncing it out. | Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs. | |
| External tables Reference external files for bulk load paths alongside row-level syncs. | Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly. | |
| Rows Read and written by key; distribution keys determine where rows live. | Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems. | |
| Databases Top-level containers that scope a sync connection. | Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data. | |
| Schemas Namespace tables and control which objects a sync can see. | Views Standard SQL views used to shape or filter data for consumers. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Greenplum–TimescaleDB connection.
Changes in Greenplum or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Greenplum or TimescaleDB data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Greenplum or TimescaleDB record.
Track your Greenplum ⇄ TimescaleDB sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Greenplum and TimescaleDB.
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 Greenplum and TimescaleDB 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 Greenplum and TimescaleDB 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 Greenplum and TimescaleDB: authenticate both systems, choose the objects to sync (such as Greenplum's Partitions and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
Yes — Stacksync ships production-grade connectors for both Greenplum and TimescaleDB. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Greenplum: Polling with timestamp or key-based cursors; Greenplum does not expose logical-decoding CDC. On TimescaleDB: Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must be remapped to the parent — or timestamp-based polling on time columns; regular Postgres tables replicate through standard logical replication. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Greenplum side: Databases, Schemas, Tables, Partitions, plus custom fields where Greenplum exposes them. On the TimescaleDB side: Chunks, Continuous Aggregates, Regular PostgreSQL Tables, Views. 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.
Common patterns for Greenplum and TimescaleDB: Serve warehouse results at database speed; Fresh analytics without loading windows; Offload heavy reads. Aggregates or model outputs computed in Greenplum sync into TimescaleDB, where whatever reads from that database gets them without querying the warehouse.
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 386 integrations available for Greenplum and TimescaleDB.