Two-way sync
Changes in Azure Synapse Analytics or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.
Keep Azure Synapse Analytics 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 Azure Synapse Analytics, 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 Azure Synapse Analytics in real time, and result tables in Azure Synapse Analytics sync back into TimescaleDB, with schema and type mapping between the two systems handled for you.
Aggregates or model outputs computed in Azure Synapse Analytics 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 Azure Synapse Analytics 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.
| Azure Synapse Analytics objects | TimescaleDB objects | |
|---|---|---|
| Tables (dedicated SQL pool) Distributed warehouse tables that serve as sync destinations for analytics workloads. | Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs. | |
| External tables Tables over files in the data lake, queried through serverless SQL and often read-only in syncs. | Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly. | |
| Views Curated projections used when downstream tools should not read base tables directly. | Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems. | |
| Schemas Namespaces that separate staging, integration, and presentation layers. | Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data. | |
| Materialized views Precomputed aggregates that speed reads of frequently synced result sets. | Views Standard SQL views used to shape or filter data for consumers. | |
| SQL pools Dedicated or serverless compute contexts that determine how and where queries run. | Schemas Postgres namespaces used to separate synced datasets by team or environment. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Azure Synapse Analytics–TimescaleDB connection.
Changes in Azure Synapse Analytics or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Azure Synapse Analytics 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 Azure Synapse Analytics or TimescaleDB record.
Track your Azure Synapse Analytics ⇄ TimescaleDB sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Azure Synapse Analytics 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 Azure Synapse Analytics 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 Azure Synapse Analytics 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 Azure Synapse Analytics and TimescaleDB: authenticate both systems, choose the objects to sync (such as Azure Synapse Analytics's Tables (dedicated SQL pool) and External tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the Azure Synapse Analytics side: Schemas, Materialized views, SQL pools, Tables (dedicated SQL pool), plus custom fields where Azure Synapse Analytics exposes them. On the TimescaleDB side: Regular PostgreSQL Tables, Views, Schemas, Hypertables. 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 Azure Synapse Analytics and TimescaleDB: Serve warehouse results at database speed; Fresh analytics without loading windows; Offload heavy reads. Aggregates or model outputs computed in Azure Synapse Analytics sync into TimescaleDB, where whatever reads from that database gets them without querying the warehouse.
Azure Synapse Analytics: SQL wire protocol (TDS) with T-SQL for SQL pools; additional Spark and pipeline surfaces exist but syncs use the SQL endpoint. Authentication: SQL authentication or Microsoft Entra ID. TimescaleDB: SQL wire protocol (PostgreSQL). Authentication: Database credentials. Stacksync manages authentication, retries, and rate limits on both sides.
Azure Synapse Analytics: Dedicated SQL pool tables are distributed across compute nodes using hash, round-robin, or replicated strategies, and the choice affects load and query performance for synced tables. TimescaleDB: TimescaleDB is packaged as a PostgreSQL extension, so standard Postgres drivers and SQL tooling work unchanged. Stacksync's field mapping accounts for these differences between Azure Synapse Analytics and TimescaleDB without custom code.
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 Azure Synapse Analytics and TimescaleDB.