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Database ⇄ Data warehouse

Amazon DynamoDB to ClickHouse integration — real-time, two-way sync

Keep Amazon DynamoDB and ClickHouse in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Why teams connect Amazon DynamoDB and ClickHouse

Connect Amazon DynamoDB 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 Amazon DynamoDB'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 Amazon DynamoDB where the services that read from it get them at normal query latency.

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

Common use cases

  • 01 Land product event data alongside synced CRM accounts so analysts join usage and revenue in one place.
  • 02 Sync aggregated ClickHouse query results back into operational tools, such as account-level usage metrics into a CRM.
  • 03 Use DynamoDB Streams as a change-data-capture source to push item INSERT, MODIFY, and REMOVE events into a CRM, search index, or operational database in near-real-time.
  • 04 Backfill or migrate records into DynamoDB from another database using BatchWriteItem, then keep the two stores in continuous sync.

Common sync patterns

Serve warehouse results at database speed

Aggregates or model outputs computed in ClickHouse sync into Amazon DynamoDB, where whatever reads from that database gets them without querying the warehouse.

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 Amazon DynamoDB focused on its operational workload.

What you can sync between Amazon DynamoDB and ClickHouse

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.

Amazon DynamoDB objects ClickHouse objects How this pairing syncs
Items Individual schemaless records (attributes up to 400 KB each); read with GetItem, Query, and Scan and written with PutItem or BatchWriteItem, so write is supported here. Dictionaries In-memory lookup structures refreshed from external sources, sometimes fed by syncs. Items is specific to Amazon DynamoDB and Dictionaries to ClickHouse — each maps to any object or custom field on the other side.
Global secondary indexes (GSIs) Alternate key projections that let you Query by non-key attributes without a full table Scan; read-only views maintained automatically by DynamoDB. Tables (MergeTree family) Columnar, append-optimized tables that serve as the destination for high-volume sync loads. Global secondary indexes (GSIs) is specific to Amazon DynamoDB and Tables (MergeTree family) to ClickHouse — each maps to any object or custom field on the other side.
Local secondary indexes (LSIs) Extra sort keys within the same partition key, defined at table creation; queried like the base table for alternate access patterns. Databases Namespaces that group tables and scope permissions for sync users. Local secondary indexes (LSIs) is specific to Amazon DynamoDB and Databases to ClickHouse — each maps to any object or custom field on the other side.
DynamoDB Streams Ordered item-level change records (INSERT, MODIFY, REMOVE) with old/new image views and 24-hour retention; the native change-data-capture source Stacksync reads for near-real-time sync. Views Saved queries used as curated, read-only sync sources. DynamoDB Streams is specific to Amazon DynamoDB and Views to ClickHouse — each maps to any object or custom field on the other side.
Global Tables Multi-region, active-active replicas of a table kept in sync by DynamoDB; each region is read and written locally with last-writer-wins conflict resolution. Materialized views Insert-time transformations that reshape incoming synced rows into aggregates. Global Tables is specific to Amazon DynamoDB and Materialized views to ClickHouse — each maps to any object or custom field on the other side.
Time to Live (TTL) Per-item expiry timestamps; DynamoDB deletes expired items in the background and emits a Streams REMOVE record for each deletion. Distributed tables Query-routing tables over cluster shards in self-managed deployments. Time to Live (TTL) is specific to Amazon DynamoDB and Distributed tables to ClickHouse — each maps to any object or custom field on the other side.

How changes propagate between Amazon DynamoDB and ClickHouse

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.

Amazon DynamoDB ClickHouse Sub-second propagation

DetectionChanges in Amazon DynamoDB are captured at the source via change data capture — no polling loop against its API. DynamoDB Streams emit ordered item-level change records (INSERT, MODIFY, REMOVE) with KEYS_ONLY, NEW_IMAGE, OLD_IMAGE, or NEW_AND_OLD_IMAGES views.

DeliveryEach detected change is applied to ClickHouse as a row-level write, with types converted between the two schemas.

ClickHouse Amazon DynamoDB Interval-based propagation

DetectionStacksync polls ClickHouse for changes on an incremental schedule, reading only records changed since the previous pass. No log-based CDC for consumers.

DeliveryEach detected change is applied to Amazon DynamoDB as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Amazon DynamoDB: Throughput is metered in read/write capacity units (provisioned or on-demand): 1 WCU = one 1 KB write per second, 1 RCU = one strongly-consistent 4 KB read per second. Exceeding capacity or the ~3,000 RCU / 1,000 WCU per-partition ceiling returns ProvisionedThroughputExceededException with throttling.
What ships with Amazon DynamoDB ⇄ ClickHouse

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon DynamoDB or ClickHouse 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 Amazon DynamoDB or ClickHouse record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Amazon DynamoDB and ClickHouse connectors work

Amazon DynamoDB

Integration surface
AWS SDK / low-level HTTPS JSON API at dynamodb.<region>.amazonaws.com (PutItem, GetItem, UpdateItem, DeleteItem, Query, Scan, BatchWriteItem, TransactWriteItems), plus PartiQL (ExecuteStatement) for SQL-style access and DynamoDB Streams for change capture.
Authentication
AWS Signature Version 4 (SigV4) signed requests using an IAM access key ID and secret key, or temporary STS credentials from an assumed IAM role; IAM policies scope access down to table and item level.
Change detection
DynamoDB Streams emit ordered item-level change records (INSERT, MODIFY, REMOVE) with KEYS_ONLY, NEW_IMAGE, OLD_IMAGE, or NEW_AND_OLD_IMAGES views and 24-hour retention, read via shard iterators (or Kinesis Data Streams for longer retention). No native HTTP webhooks.
Capabilities
read · write · CDC
Rate limits
Throughput is metered in read/write capacity units (provisioned or on-demand): 1 WCU = one 1 KB write per second, 1 RCU = one strongly-consistent 4 KB read per second. Exceeding capacity or the ~3,000 RCU / 1,000 WCU per-partition ceiling returns ProvisionedThroughputExceededException with throttling.

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
How it works

How to connect Amazon DynamoDB to ClickHouse — 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 Amazon DynamoDB and ClickHouse 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
    Amazon DynamoDB connected
    ClickHouse connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon DynamoDB and ClickHouse 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 · Amazon DynamoDB ⇄ ClickHouse
    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
    Amazon DynamoDB ClickHouse
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon DynamoDB and ClickHouse integration FAQ

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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.

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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 572 integrations available for Amazon DynamoDB and ClickHouse.

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