Two-way sync
Changes in Azure Synapse Analytics or Neo4j instantly reflect in both systems. No stale data, no manual imports.
Keep Azure Synapse Analytics and Neo4j 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 Neo4j'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 Neo4j where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Neo4j sync into Azure Synapse Analytics in real time, and result tables in Azure Synapse Analytics sync back into Neo4j, with schema and type mapping between the two systems handled for you.
Point analytical queries at the synced copy in Azure Synapse Analytics and keep Neo4j focused on its operational workload.
Rows from Neo4j land in Azure Synapse Analytics as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in Azure Synapse Analytics sync into Neo4j, where whatever reads from that database gets them without querying the warehouse.
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 | Neo4j objects | |
|---|---|---|
| External tables Tables over files in the data lake, queried through serverless SQL and often read-only in syncs. | Relationships Typed, directed edges that carry the connections syncs exist to model. | |
| Views Curated projections used when downstream tools should not read base tables directly. | Properties Key-value attributes on both nodes and relationships, mapped from source fields. | |
| Schemas Namespaces that separate staging, integration, and presentation layers. | Labels Node type markers used to map source tables or objects onto the graph. | |
| Materialized views Precomputed aggregates that speed reads of frequently synced result sets. | Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. | |
| SQL pools Dedicated or serverless compute contexts that determine how and where queries run. | Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. | |
| Tables (dedicated SQL pool) Distributed warehouse tables that serve as sync destinations for analytics workloads. | Users & Roles Security principals controlling what an integration credential can query or modify. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Azure Synapse Analytics–Neo4j connection.
Changes in Azure Synapse Analytics or Neo4j instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Azure Synapse Analytics or Neo4j 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 Neo4j record.
Track your Azure Synapse Analytics ⇄ Neo4j sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Azure Synapse Analytics and Neo4j.
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 Neo4j 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 Neo4j 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 Neo4j: authenticate both systems, choose the objects to sync (such as Azure Synapse Analytics's External tables and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
Common patterns for Azure Synapse Analytics and Neo4j: Offload heavy reads; Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed. Point analytical queries at the synced copy in Azure Synapse Analytics and keep Neo4j focused on its operational workload.
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. Neo4j: Bolt binary protocol with Cypher via official drivers, plus an HTTP query API. Authentication: Username/password (basic auth); enterprise deployments add SSO options. 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. Neo4j: Client drivers connect over the Bolt binary protocol rather than HTTP for query workloads. Stacksync's field mapping accounts for these differences between Azure Synapse Analytics and Neo4j 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 Synapse Analytics and Neo4j records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Azure Synapse Analytics and Neo4j connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Azure Synapse Analytics–Neo4j 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 Synapse Analytics and Neo4j.