Two-way sync
Changes in TimescaleDB or Yellowbrick instantly reflect in both systems. No stale data, no manual imports.
Keep TimescaleDB and Yellowbrick 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 Yellowbrick, 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 Yellowbrick in real time, and result tables in Yellowbrick sync back into TimescaleDB, with schema and type mapping between the two systems handled for you.
Aggregates or model outputs computed in Yellowbrick 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 Yellowbrick 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.
| TimescaleDB objects | Yellowbrick objects | |
|---|---|---|
| Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems. | Schemas Namespaces used to organize synced datasets by source or domain. | |
| Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data. | Tables Columnar MPP tables; the primary targets for warehouse syncs. | |
| Views Standard SQL views used to shape or filter data for consumers. | Views Logical views used to shape reads for BI and downstream syncs. | |
| Schemas Postgres namespaces used to separate synced datasets by team or environment. | Users and Roles Access-control objects that govern what a sync service account can read and write. | |
| Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs. | Databases Top-level containers for schemas and tables. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every TimescaleDB–Yellowbrick connection.
Changes in TimescaleDB or Yellowbrick instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever TimescaleDB or Yellowbrick data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single TimescaleDB or Yellowbrick record.
Track your TimescaleDB ⇄ Yellowbrick sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between TimescaleDB and Yellowbrick.
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 TimescaleDB and Yellowbrick 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 TimescaleDB and Yellowbrick 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 TimescaleDB and Yellowbrick: authenticate both systems, choose the objects to sync (such as TimescaleDB's Continuous Aggregates and Regular PostgreSQL Tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection 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. On Yellowbrick: Polling on timestamp columns; no exposed transaction-log CDC. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Yellowbrick side: Schemas, Tables, Views, Users and Roles, plus custom fields where Yellowbrick exposes them. On the TimescaleDB side: Views, Schemas, Hypertables, Chunks. 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 TimescaleDB and Yellowbrick: Serve warehouse results at database speed; Fresh analytics without loading windows; Offload heavy reads. Aggregates or model outputs computed in Yellowbrick sync into TimescaleDB, where whatever reads from that database gets them without querying the warehouse.
TimescaleDB: SQL wire protocol (PostgreSQL). Authentication: Database credentials. Yellowbrick: SQL wire protocol (PostgreSQL-compatible) with JDBC/ODBC drivers; bulk loading via the ybload utility. Authentication: Database credentials, with LDAP and Kerberos options in enterprise deployments. Stacksync manages authentication, retries, and rate limits on both sides.
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 TimescaleDB and Yellowbrick.