Two-way sync
Changes in Amazon DynamoDB or Citus instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon DynamoDB and Citus in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
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 Amazon DynamoDB and Citus 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.
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
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 | Citus objects | How this pairing syncs | |
|---|---|---|---|
| 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. | Reference tables Small lookup tables replicated to every node, synced like ordinary Postgres tables. | Global secondary indexes (GSIs) is specific to Amazon DynamoDB and Reference tables to Citus — 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. | Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. | Local secondary indexes (LSIs) is specific to Amazon DynamoDB and Local tables to Citus — 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. | Schemas Standard Postgres namespaces used to scope what a sync user can read and write. | DynamoDB Streams is specific to Amazon DynamoDB and Schemas to Citus — 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. | Views Curated projections over distributed data, often used as read-only sync sources. | Global Tables is specific to Amazon DynamoDB and Views to Citus — 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. | Sequences Key generators that matter when external writes must not collide with application inserts. | Time to Live (TTL) is specific to Amazon DynamoDB and Sequences to Citus — each maps to any object or custom field on the other side. | |
| 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. | Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. | Tables is specific to Amazon DynamoDB and Distributed tables to Citus — 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 Citus as a row-level write, with types converted between the two schemas.
DetectionChanges in Citus are captured at the source via change data capture — no polling loop against its API. PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres.
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–Citus connection.
Changes in Amazon DynamoDB or Citus instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon DynamoDB or Citus 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 Citus record.
Track your Amazon DynamoDB ⇄ Citus sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon DynamoDB and Citus.
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 Citus 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 Citus 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 Citus: authenticate both systems, choose the objects to sync (such as Amazon DynamoDB's Global secondary indexes (GSIs) and Local secondary indexes (LSIs)), map fields visually, and changes propagate both ways in milliseconds — no code required.
Yes — Stacksync ships production-grade connectors for both Amazon DynamoDB and Citus. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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 Citus: PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Amazon DynamoDB side: Tables, Items, Global secondary indexes (GSIs), Local secondary indexes (LSIs), plus custom fields where Amazon DynamoDB exposes them. On the Citus side: Sequences, Distributed tables, Reference tables, Local tables. 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 Citus: Migration with zero-downtime cutover; Shared reference data between services; Regional or environment copies. When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
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 464 integrations available for Amazon DynamoDB and Citus.