Two-way sync
Changes in Azure Cosmos DB or Databricks instantly reflect in both systems. No stale data, no manual imports.
Keep Azure Cosmos DB and Databricks 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 Azure Cosmos DB's rows in Databricks, 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 Azure Cosmos DB where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Azure Cosmos DB sync into Databricks in real time, and result tables in Databricks sync back into Azure Cosmos DB, with schema and type mapping between the two systems handled for you.
Rows from Azure Cosmos DB land in Databricks as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in Databricks sync into Azure Cosmos DB, 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.
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 Cosmos DB objects | Databricks objects | |
|---|---|---|
| Databases Top-level namespaces that scope containers and throughput provisioning. | Delta Tables The primary read and write target; operational data lands here as managed or external tables. | |
| Containers The unit of partitioning and throughput; each container maps to a synced collection. | Views Curated read-only projections used as sync sources for downstream tools. | |
| Items (JSON documents) Schema-flexible JSON records read and written during sync; nested structures are flattened or mapped as needed. | Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. | |
| Partition keys Determine data distribution and must be included on writes for the sync to route items correctly. | Volumes Unity Catalog file storage used for staging bulk loads. | |
| Change feed entries Ordered record of inserts and updates per partition, consumed for incremental sync. | SQL Warehouses The compute endpoint a sync connects to for query execution. | |
| Stored procedures and triggers Server-side logic scoped to a partition; relevant when writes must respect existing validation. | Change Data Feed Row-level change records on Delta tables that drive incremental reads. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Azure Cosmos DB–Databricks connection.
Changes in Azure Cosmos DB or Databricks instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Azure Cosmos DB or Databricks 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 Cosmos DB or Databricks record.
Track your Azure Cosmos DB ⇄ Databricks sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Azure Cosmos DB and Databricks.
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 Cosmos DB and Databricks 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 Cosmos DB and Databricks 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 Cosmos DB and Databricks: authenticate both systems, choose the objects to sync (such as Azure Cosmos DB's Databases and Containers), map fields visually, and changes propagate both ways in milliseconds — no code required.
Common patterns for Azure Cosmos DB and Databricks: Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed; Fresh analytics without loading windows. Rows from Azure Cosmos DB land in Databricks as they change, replacing hand-built CDC and batch extract jobs.
Azure Cosmos DB: REST API and SDKs over HTTPS (API for NoSQL, formerly the SQL API); also MongoDB, Cassandra, Gremlin, and Table API surfaces. Authentication: Account keys, resource tokens, or Microsoft Entra ID role-based access. Databricks: SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution. Authentication: Personal access tokens or OAuth machine-to-machine credentials for service principals. Stacksync manages authentication, retries, and rate limits on both sides.
Databricks: Delta Lake's Change Data Feed records row-level inserts, updates, and deletes, enabling incremental sync without full scans. Azure Cosmos DB: Throughput is provisioned in request units per container or database, which means sync read and write volume has a direct cost and throttling dimension. Stacksync's field mapping accounts for these differences between Azure Cosmos DB and Databricks without custom code.
Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Azure Cosmos DB and Databricks records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Azure Cosmos DB and Databricks connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Azure Cosmos DB–Databricks integration in-house.
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 Cosmos DB and Databricks.