Two-way sync
Changes in Materialize or VoltDB instantly reflect in both systems. No stale data, no manual imports.
Keep Materialize and VoltDB 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 VoltDB'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 VoltDB where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in VoltDB sync into Materialize in real time, and result tables in Materialize sync back into VoltDB, with schema and type mapping between the two systems handled for you.
Aggregates or model outputs computed in Materialize sync into VoltDB, 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 Materialize and keep VoltDB 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.
| Materialize objects | VoltDB objects | How this pairing syncs | |
|---|---|---|---|
| Materialized Views Incrementally maintained query results that syncs read as continuously up-to-date datasets. | Materialized Views Synchronously maintained aggregates over tables, useful as pre-computed read sources. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Sources Ingestion points (Kafka, Postgres CDC, MySQL CDC, webhook) that feed external data into Materialize. | Stored Procedures Precompiled transactional units that serve as the primary write interface. | Sources is specific to Materialize and Stored Procedures to VoltDB — each maps to any object or custom field on the other side. | |
| Sinks Outbound connections that emit view changes to Kafka topics. | Streams Insert-only constructs that feed the export subsystem with committed rows. | Sinks is specific to Materialize and Streams to VoltDB — each maps to any object or custom field on the other side. | |
| Indexes In-memory arrangements that make view reads fast for serving workloads. | Export Targets and Topics Connectors that push committed data to external systems such as Kafka or JDBC sinks. | Indexes is specific to Materialize and Export Targets and Topics to VoltDB — each maps to any object or custom field on the other side. | |
| Clusters Compute pools that isolate ingestion, view maintenance, and serving. | Partitioned Tables Tables sharded across partitions by a partitioning column; the primary transactional store and sync target. | Clusters is specific to Materialize and Partitioned Tables to VoltDB — each maps to any object or custom field on the other side. | |
| Connections & Secrets Stored credentials and endpoints used by sources and sinks. | Replicated Tables Small reference tables copied to every partition, a common landing spot for synced lookup data. | Connections & Secrets is specific to Materialize and Replicated Tables to VoltDB — 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.
DetectionChanges in Materialize are captured at the source via change data capture — no polling loop against its API. SUBSCRIBE queries stream row-level changes of any view or table to the client.
DeliveryEach detected change is applied to VoltDB as a row-level write, with types converted between the two schemas.
DetectionStacksync polls VoltDB for changes on an incremental schedule, reading only records changed since the previous pass. Export streams and topics push committed changes to configured targets.
DeliveryEach detected change is applied to Materialize as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Materialize–VoltDB connection.
Changes in Materialize or VoltDB instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Materialize or VoltDB data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Materialize or VoltDB record.
Track your Materialize ⇄ VoltDB sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Materialize and VoltDB.
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 Materialize and VoltDB 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 Materialize and VoltDB 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 Materialize and VoltDB: authenticate both systems, choose the objects to sync (such as Materialize's Materialized Views and Sources), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Materialize: SUBSCRIBE queries stream row-level changes of any view or table to the client. On VoltDB: Export streams and topics push committed changes to configured targets; otherwise polling. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Materialize side: Indexes, Clusters, Connections & Secrets, Schemas & Databases, plus custom fields where Materialize exposes them. On the VoltDB side: Partitioned Tables, Replicated Tables, Stored Procedures, Materialized Views. 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 Materialize and VoltDB: Serve warehouse results at database speed; Fresh analytics without loading windows; Offload heavy reads. Aggregates or model outputs computed in Materialize sync into VoltDB, where whatever reads from that database gets them without querying the warehouse.
Materialize: PostgreSQL wire protocol (SQL). Authentication: Database credentials (username/password; app passwords in the managed cloud service). VoltDB: SQL over JDBC plus native client libraries and an HTTP/JSON interface. Authentication: Database credentials. 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 392 integrations available for Materialize and VoltDB.