Real-time
Two-way sync
Changes in Materialize or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
Materialize to TimescaleDB integration — real-time, two-way sync
Keep Materialize 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.
- 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
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Migrated from Matillion
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Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Materialize and TimescaleDB
Connect TimescaleDB and Materialize 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 TimescaleDB's rows in Materialize, 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 Materialize in real time, and result tables in Materialize sync back into TimescaleDB, with schema and type mapping between the two systems handled for you.
Common use cases
- Maintain real-time inventory, usage, or account-health counters consumed by customer-facing applications.
- Bridge streaming sources and non-streaming destinations by materializing joins across both.
- Replicate subscription and billing events from operational Postgres tables into Timescale hypertables for time-series analysis.
- Keep device or asset reference tables bi-directionally in sync between TimescaleDB and an ERP.
Operational data in the warehouse, minus the pipeline
Rows from TimescaleDB land in Materialize as they change, replacing hand-built CDC and batch extract jobs.
Serve warehouse results at database speed
Aggregates or model outputs computed in Materialize sync into TimescaleDB, where whatever reads from that database gets them without querying the warehouse.
Fresh analytics without loading windows
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
What you can sync between Materialize and TimescaleDB
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.
| Materialize objects | TimescaleDB objects | |
|---|---|---|
| Tables User-managed tables that accept INSERT/UPDATE/DELETE from sync pipelines. | Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs. | |
| Sources Ingestion points (Kafka, Postgres CDC, MySQL CDC, webhook) that feed external data into Materialize. | Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly. | |
| Materialized Views Incrementally maintained query results that syncs read as continuously up-to-date datasets. | Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems. | |
| Sinks Outbound connections that emit view changes to Kafka topics. | Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data. | |
| Indexes In-memory arrangements that make view reads fast for serving workloads. | Views Standard SQL views used to shape or filter data for consumers. | |
| Clusters Compute pools that isolate ingestion, view maintenance, and serving. | Schemas Postgres namespaces used to separate synced datasets by team or environment. |
What ships with Materialize ⇄ TimescaleDB
Connect Materialize and TimescaleDB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Materialize–TimescaleDB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Materialize or TimescaleDB 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 Materialize or TimescaleDB record.
Observability
Monitoring
Track your Materialize ⇄ TimescaleDB sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Materialize and TimescaleDB.
How the Materialize and TimescaleDB connectors work
Materialize
- Integration surface
- PostgreSQL wire protocol (SQL)
- Authentication
- Database credentials (username/password; app passwords in the managed cloud service)
- Change detection
- SUBSCRIBE queries stream row-level changes of any view or table to the client
- Capabilities
- read · write · CDC
TimescaleDB
- Integration surface
- SQL wire protocol (PostgreSQL)
- Authentication
- Database credentials
- Change detection
- 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
- Capabilities
- read · write · CDC
- Rate limits
- No API rate limits; throughput is bounded by database resources and connection limits.
How it works
How to connect Materialize to TimescaleDB — 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 Materialize 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.
Materialize
connected
TimescaleDB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Materialize 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.
objects · Materialize ⇄ TimescaleDBCustomers 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.
Materialize TimescaleDBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Materialize and TimescaleDB integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Materialize and TimescaleDB: authenticate both systems, choose the objects to sync (such as Materialize's Tables and Sources), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Materialize and TimescaleDB connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Materialize–TimescaleDB integration in-house.
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Yes — Stacksync ships production-grade connectors for both Materialize and TimescaleDB. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Materialize: SUBSCRIBE queries stream row-level changes of any view or table to the client. 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.
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On the Materialize side: Connections & Secrets, Schemas & Databases, Tables, Sources, plus custom fields where Materialize exposes them. On the TimescaleDB side: Hypertables, Chunks, Continuous Aggregates, Regular PostgreSQL Tables. Stacksync auto-detects both schemas and converts types between the two systems.
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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 love 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
CSA STAR
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 386 integrations available for Materialize and TimescaleDB.
Popular · 8 of 386
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Materialize ⇄ InfluxDB -
Materialize ⇄ InterSystems IRIS -
Materialize ⇄ MarkLogic -
Materialize ⇄ Neo4j -
TimescaleDB ⇄ Greenplum -
TimescaleDB ⇄ IBM Netezza -
TimescaleDB ⇄ Rockset -
TimescaleDB ⇄ Starburst Enterprise
No integrations match .
