Real-time
Two-way sync
Changes in DuckDB or SingleStore instantly reflect in both systems. No stale data, no manual imports.
Database
DuckDB to SingleStore integration — real-time, two-way sync
Keep DuckDB and SingleStore in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect DuckDB and SingleStore
Keep DuckDB and SingleStore synchronized in real time, across engines, regions, or services, in one or both directions.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between DuckDB and SingleStore continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Common use cases
- 01 Sync SaaS data to Parquet on object storage and query it with DuckDB without standing up a warehouse.
- 02 Push aggregates computed in DuckDB out to a CRM or business tools so analysis results reach operational systems.
- 03 Feed synced operational data into applications that need low-latency responses over fresh data.
- 04 Mirror CRM and SaaS objects into SingleStore tables to serve low-latency operational dashboards.
Common sync patterns
Shared reference data between services
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
Regional or environment copies
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
Cross-engine sync
Keep the same dataset live in both DuckDB and SingleStore, so each workload runs on the engine that suits it.
What you can sync between DuckDB and SingleStore
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.
| DuckDB objects | SingleStore objects | How this pairing syncs | |
|---|---|---|---|
| Views SQL views used to shape or filter data for downstream consumers. | Views Read-only projections used as curated sync sources. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Tables Columnar tables created via SQL; the destination for materialized sync data. | Stored Procedures Existing logic sometimes invoked on write paths. | Tables is specific to DuckDB and Stored Procedures to SingleStore — each maps to any object or custom field on the other side. | |
| External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. | Indexes and Shard Keys Determine data distribution and lookup speed for sync match keys. | External files (Parquet/CSV/JSON) is specific to DuckDB and Indexes and Shard Keys to SingleStore — each maps to any object or custom field on the other side. | |
| Attached databases Additional database files or external systems attached into one session for cross-source queries. | Databases The connection target containing the tables a sync addresses. | Attached databases is specific to DuckDB and Databases to SingleStore — each maps to any object or custom field on the other side. | |
| Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. | Tables (rowstore and columnstore) Primary read/write target; storage type affects whether a table suits point lookups or scans. | Database files is specific to DuckDB and Tables (rowstore and columnstore) to SingleStore — each maps to any object or custom field on the other side. | |
| Schemas Namespaces within a database used to organize tables in sync outputs. | Reference Tables Small tables replicated to every node, often used for dimension data in syncs. | Schemas is specific to DuckDB and Reference Tables to SingleStore — each maps to any object or custom field on the other side. |
How changes propagate between DuckDB and SingleStore
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.
DuckDB SingleStore Interval-based propagation
DetectionStacksync polls DuckDB for changes on an incremental schedule, reading only records changed since the previous pass. Polling or full re-reads.
DeliveryEach detected change is applied to SingleStore as a row-level write, with types converted between the two schemas.
SingleStore DuckDB Interval-based propagation
DetectionStacksync polls SingleStore for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp or watermark columns.
DeliveryEach detected change is applied to DuckDB as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- DuckDB: No API rate limits; throughput is bounded by local compute and I/O.
- SingleStore: No API rate limits; throughput is bounded by workspace or cluster size.
What ships with DuckDB ⇄ SingleStore
Connect DuckDB and SingleStore for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every DuckDB–SingleStore connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever DuckDB or SingleStore data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
At scale
Event queues
Handle millions of events per minute without losing a single DuckDB or SingleStore record.
Observability
Monitoring
Track your DuckDB ⇄ SingleStore sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between DuckDB and SingleStore.
How the DuckDB and SingleStore connectors work
DuckDB
- Integration surface
- In-process SQL engine via client libraries (Python, Node.js, JDBC, CLI); no server or network API by default
- Authentication
- None built in; access control is file-system level (MotherDuck adds token auth for its hosted service)
- Change detection
- Polling or full re-reads; no change feed or transaction log API
- Capabilities
- read · write
- Rate limits
- No API rate limits; throughput is bounded by local compute and I/O
SingleStore
- Integration surface
- SQL over the MySQL wire protocol; an HTTP Data API is also available for SQL over REST
- Authentication
- Database credentials
- Change detection
- Polling on timestamp or watermark columns; the platform also provides change-observation features in recent versions
- Capabilities
- read · write
- Rate limits
- No API rate limits; throughput is bounded by workspace or cluster size
How it works
How to connect DuckDB to SingleStore — three steps, no code
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.
- 01
Connect your apps
Authenticate DuckDB and SingleStore with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
DuckDB
connected
SingleStore
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the DuckDB and SingleStore 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.
objects · DuckDB ⇄ SingleStoreCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
DuckDB SingleStoreCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
DuckDB and SingleStore integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between DuckDB and SingleStore: authenticate both systems, choose the objects to sync (such as DuckDB's Views and Tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
DuckDB: It queries Parquet, CSV, and JSON files directly without importing them, which makes file-based exchange a natural sync pattern. SingleStore: Native Pipelines ingest continuously from Kafka and object storage, so external syncs typically cover the SaaS and database sources Pipelines do not. Stacksync's field mapping accounts for these differences between DuckDB and SingleStore 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 DuckDB and SingleStore records are not retained after a sync operation.
-
Stacksync pricing is usage-based and starts at $1,000/month, including the managed DuckDB and SingleStore connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom DuckDB–SingleStore integration in-house.
-
Yes — Stacksync ships production-grade connectors for both DuckDB and SingleStore. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
-
Change detection on DuckDB: Polling or full re-reads; no change feed or transaction log API. On SingleStore: Polling on timestamp or watermark columns; the platform also provides change-observation features in recent versions. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
SECURITY
Security teams trust Stacksync
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.
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS
SSO & SCIM
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Alerts
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Secure connection options
Securely connects to your systems with:
Related integrations
Every pair below is a real-time, two-way sync. Search all 391 integrations available for DuckDB and SingleStore.
Popular · 4 of 391
No integrations match .
