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Data warehouse ⇄ Database

ClickHouse to SingleStore integration — real-time, two-way sync

Keep ClickHouse 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

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Why teams connect ClickHouse and SingleStore

Connect SingleStore and ClickHouse with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Operational databases and analytical warehouses want the same data at different moments. Analysts want SingleStore's rows in ClickHouse, 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 SingleStore where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in SingleStore sync into ClickHouse in real time, and result tables in ClickHouse sync back into SingleStore, with schema and type mapping between the two systems handled for you.

Common use cases

  • Sync aggregated ClickHouse query results back into operational tools, such as account-level usage metrics into a CRM.
  • Consolidate logs and business records from multiple sources into MergeTree tables for retention and reporting.
  • Mirror CRM and SaaS objects into SingleStore tables to serve low-latency operational dashboards.
  • Sync results of real-time analytical queries back into business tools where teams act on them.

Fresh analytics without loading windows

Because changes stream continuously, analysts query current data instead of waiting for last night's load.

Offload heavy reads

Point analytical queries at the synced copy in ClickHouse and keep SingleStore focused on its operational workload.

Operational data in the warehouse, minus the pipeline

Rows from SingleStore land in ClickHouse as they change, replacing hand-built CDC and batch extract jobs.

What you can sync between ClickHouse 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.

ClickHouse objects SingleStore objects
Dictionaries In-memory lookup structures refreshed from external sources, sometimes fed by syncs. Pipelines Native ingestion jobs from Kafka or object storage that coexist with external syncs.
Tables (MergeTree family) Columnar, append-optimized tables that serve as the destination for high-volume sync loads. Stored Procedures Existing logic sometimes invoked on write paths.
Databases Namespaces that group tables and scope permissions for sync users. Indexes and Shard Keys Determine data distribution and lookup speed for sync match keys.
Views Saved queries used as curated, read-only sync sources. Databases The connection target containing the tables a sync addresses.
Materialized views Insert-time transformations that reshape incoming synced rows into aggregates. Tables (rowstore and columnstore) Primary read/write target; storage type affects whether a table suits point lookups or scans.
Distributed tables Query-routing tables over cluster shards in self-managed deployments. Views Read-only projections used as curated sync sources.
What ships with ClickHouse ⇄ SingleStore

Connect ClickHouse and SingleStore for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every ClickHouse–SingleStore connection.

Real-time

Two-way sync

Changes in ClickHouse or SingleStore instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever ClickHouse 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 ClickHouse or SingleStore record.

Observability

Monitoring

Track your ClickHouse ⇄ SingleStore sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between ClickHouse and SingleStore.

How the ClickHouse and SingleStore connectors work

ClickHouse

Integration surface
Native TCP protocol and HTTP interface; standard SQL dialect, with MySQL and PostgreSQL wire compatibility available
Authentication
Database credentials (username/password); ClickHouse Cloud issues per-service credentials over TLS
Change detection
No log-based CDC for consumers; incremental reads use polling on monotonic columns, and ClickHouse is usually the destination rather than the source
Capabilities
read · write

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 ClickHouse 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.

  1. 01

    Connect your apps

    Authenticate ClickHouse 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.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    ClickHouse connected
    SingleStore connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the ClickHouse 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · ClickHouse ⇄ SingleStore
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    ClickHouse SingleStore
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

ClickHouse and SingleStore integration FAQ

SECURITY

Security teams love 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.

Learn more about security
SOC 2 type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 386 integrations available for ClickHouse and SingleStore.

Popular · 8 of 386
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