Two-way sync
Changes in Apache Druid or Azure Synapse Analytics instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Druid and Azure Synapse Analytics in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Companies end up with two warehouses for practical reasons: a migration in progress, teams that standardized on different platforms, an acquisition, or tools that only connect to one of them. The result is the same dataset maintained twice, with duplicated pipelines and numbers that almost match.
Stacksync syncs tables between Apache Druid and Azure Synapse Analytics continuously, in either or both directions. Rows changed on one platform appear on the other within seconds, with schema and type mapping handled, so both warehouses answer questions with the same data.
When one platform is replacing the other, keep tables mirrored while workloads move over gradually, and cut over with nothing to backfill.
Mirror the datasets a BI tool, notebook, or application needs onto the platform it can actually reach.
Where different teams run different warehouses, sync the curated tables both rely on so their metrics agree by construction.
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.
| Apache Druid objects | Azure Synapse Analytics objects | How this pairing syncs | |
|---|---|---|---|
| Lookups Key-value mappings joined at query time, refreshable from external systems. | Views Curated projections used when downstream tools should not read base tables directly. | Lookups is specific to Apache Druid and Views to Azure Synapse Analytics — each maps to any object or custom field on the other side. | |
| Tasks Batch ingestion and compaction jobs monitored during data loads. | Schemas Namespaces that separate staging, integration, and presentation layers. | Tasks is specific to Apache Druid and Schemas to Azure Synapse Analytics — each maps to any object or custom field on the other side. | |
| Datasources The table-like unit of storage and querying, the main target of reads and ingestion. | Materialized views Precomputed aggregates that speed reads of frequently synced result sets. | Datasources is specific to Apache Druid and Materialized views to Azure Synapse Analytics — each maps to any object or custom field on the other side. | |
| Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. | SQL pools Dedicated or serverless compute contexts that determine how and where queries run. | Segments is specific to Apache Druid and SQL pools to Azure Synapse Analytics — each maps to any object or custom field on the other side. | |
| Dimensions String and categorical columns used for filtering and grouping in synced queries. | Tables (dedicated SQL pool) Distributed warehouse tables that serve as sync destinations for analytics workloads. | Dimensions is specific to Apache Druid and Tables (dedicated SQL pool) to Azure Synapse Analytics — each maps to any object or custom field on the other side. | |
| Metrics Numeric columns, often pre-aggregated at ingestion via rollup. | External tables Tables over files in the data lake, queried through serverless SQL and often read-only in syncs. | Metrics is specific to Apache Druid and External tables to Azure Synapse Analytics — each maps to any object or custom field on the other side. |
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.
DetectionStacksync polls Apache Druid for changes on an incremental schedule, reading only records changed since the previous pass. Data enters Druid through streaming or batch ingestion rather than row updates.
DeliveryEach detected change is applied to Azure Synapse Analytics as a row-level write, with types converted between the two schemas.
DetectionStacksync polls Azure Synapse Analytics for changes on an incremental schedule, reading only records changed since the previous pass. Polling on watermark columns.
DeliveryEach detected change is applied to Apache Druid as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Druid–Azure Synapse Analytics connection.
Changes in Apache Druid or Azure Synapse Analytics instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Druid or Azure Synapse Analytics data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Apache Druid or Azure Synapse Analytics record.
Track your Apache Druid ⇄ Azure Synapse Analytics sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Druid and Azure Synapse Analytics.
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 Apache Druid and Azure Synapse Analytics 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 Apache Druid and Azure Synapse Analytics 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 Apache Druid and Azure Synapse Analytics: authenticate both systems, choose the objects to sync (such as Apache Druid's Lookups and Tasks), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Apache Druid: Not applicable for reads out (polling by time interval); data enters Druid through streaming or batch ingestion rather than row updates. On Azure Synapse Analytics: Polling on watermark columns; Synapse SQL pools do not expose log-based CDC for downstream consumers. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Apache Druid side: Ingestion Supervisors, Lookups, Tasks, Datasources, plus custom fields where Apache Druid exposes them. On the Azure Synapse Analytics side: Materialized views, SQL pools, Tables (dedicated SQL pool), External tables. 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 Apache Druid and Azure Synapse Analytics: Migration without a big bang; Serve tools that only connect to one platform; Shared datasets across teams. When one platform is replacing the other, keep tables mirrored while workloads move over gradually, and cut over with nothing to backfill.
Apache Druid: REST API (SQL over HTTP and native JSON queries); JDBC via Avatica. Authentication: Deployment-dependent: basic authentication or an authenticator extension; often fronted by a proxy. 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. 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 475 integrations available for Apache Druid and Azure Synapse Analytics.