Two-way sync
Changes in Amazon DynamoDB or Apache Doris instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon DynamoDB and Apache Doris 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 Amazon DynamoDB's rows in Apache Doris, 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 Apache Doris in real time, and result tables in Apache Doris sync back into Amazon DynamoDB, with schema and type mapping between the two systems handled for you.
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Point analytical queries at the synced copy in Apache Doris and keep Amazon DynamoDB focused on its operational workload.
Rows from Amazon DynamoDB land in Apache Doris as they change, replacing hand-built CDC and batch extract jobs.
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 | Apache Doris objects | How this pairing syncs | |
|---|---|---|---|
| Tables Top-level containers, each with a partition key and optional sort key; Stacksync syncs a table as a stream of items with full read and write via PutItem, UpdateItem, and DeleteItem. | Tables Columnar tables in one of Doris's table models, used as sync destinations. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| 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. | Materialized Views Precomputed views readable for downstream syncs and BI. | DynamoDB Streams is specific to Amazon DynamoDB and Materialized Views to Apache Doris — 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. | Users and Roles Principals used to grant the sync connection scoped access. | Global Tables is specific to Amazon DynamoDB and Users and Roles to Apache Doris — 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. | Databases Logical containers that scope connections and grants. | Time to Live (TTL) is specific to Amazon DynamoDB and Databases to Apache Doris — each maps to any object or custom field on the other side. | |
| 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. | Unique Key Tables Tables supporting primary-key upserts, the natural target for row-level syncs. | Items is specific to Amazon DynamoDB and Unique Key Tables to Apache Doris — 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. | Aggregate Key Tables Tables that pre-aggregate on load, used for metric rollups. | Global secondary indexes (GSIs) is specific to Amazon DynamoDB and Aggregate Key Tables to Apache Doris — 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 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 Apache Doris as a row-level write, with types converted between the two schemas.
DetectionStacksync polls Apache Doris for changes on an incremental schedule, reading only records changed since the previous pass. Polling on partition or timestamp columns for reads.
DeliveryEach detected change is applied to Amazon DynamoDB as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon DynamoDB–Apache Doris connection.
Changes in Amazon DynamoDB or Apache Doris instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon DynamoDB or Apache Doris data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Amazon DynamoDB or Apache Doris record.
Track your Amazon DynamoDB ⇄ Apache Doris sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon DynamoDB and Apache Doris.
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 Amazon DynamoDB and Apache Doris 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 Amazon DynamoDB and Apache Doris 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 Amazon DynamoDB and Apache Doris: authenticate both systems, choose the objects to sync (such as Amazon DynamoDB's Tables and DynamoDB Streams), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Amazon DynamoDB: 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. On Apache Doris: Polling on partition or timestamp columns for reads; ingestion into Doris is push-based via load jobs. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Apache Doris side: Partitions, Materialized Views, Users and Roles, Databases, plus custom fields where Apache Doris exposes them. On the Amazon DynamoDB side: Items, Global secondary indexes (GSIs), Local secondary indexes (LSIs), DynamoDB Streams. 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 Amazon DynamoDB and Apache Doris: Fresh analytics without loading windows; Offload heavy reads; Operational data in the warehouse, minus the pipeline. Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Amazon DynamoDB: 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. Apache Doris: MySQL wire protocol for SQL access; HTTP APIs (such as Stream Load) for bulk ingestion. 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.
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Every pair below is a real-time, two-way sync. Search all 468 integrations available for Amazon DynamoDB and Apache Doris.