Two-way sync
Changes in Apache Pinot or AWS Aurora PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Pinot and AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL's rows in Apache Pinot, 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 AWS Aurora PostgreSQL where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in AWS Aurora PostgreSQL sync into Apache Pinot in real time, and result tables in Apache Pinot sync back into AWS Aurora PostgreSQL, with schema and type mapping between the two systems handled for you.
Rows from AWS Aurora PostgreSQL land in Apache Pinot as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in Apache Pinot sync into AWS Aurora PostgreSQL, where whatever reads from that database gets them without querying the warehouse.
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
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.
| Apache Pinot objects | AWS Aurora PostgreSQL objects | |
|---|---|---|
| Offline Tables Batch-loaded tables merged with real-time data at query time. | Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. | |
| Indexes Inverted, range, and star-tree indexes that determine which sync queries run at low latency. | Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. | |
| Tenants Logical groupings that isolate workloads on shared clusters. | Foreign keys Relationship metadata that syncs can translate into object references elsewhere. | |
| Tables The queryable unit, defined as offline, real-time, or hybrid; the main read target. | Replication slots and publications The logical replication objects that power log-based CDC. | |
| Schemas Column definitions (dimensions, metrics, time columns) mapped during integration setup. | Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. | |
| Segments Immutable data files that batch ingestion uploads and the cluster serves. | Tables The core sync unit; rows are matched across systems by primary key. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Pinot–AWS Aurora PostgreSQL connection.
Changes in Apache Pinot or AWS Aurora PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Pinot or AWS Aurora PostgreSQL data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Apache Pinot or AWS Aurora PostgreSQL record.
Track your Apache Pinot ⇄ AWS Aurora PostgreSQL sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Pinot and AWS Aurora PostgreSQL.
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 Apache Pinot and AWS Aurora PostgreSQL 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 Apache Pinot and AWS Aurora PostgreSQL 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 Apache Pinot and AWS Aurora PostgreSQL: authenticate both systems, choose the objects to sync (such as Apache Pinot's Offline Tables and Indexes), map fields visually, and changes propagate both ways in milliseconds — no code required.
Apache Pinot: Upsert support on real-time tables lets the latest record per primary key win, which suits syncing mutable entities from streams. AWS Aurora PostgreSQL: Replication slots retain WAL for their consumers, so an interrupted CDC sync can resume without losing changes. Stacksync's field mapping accounts for these differences between Apache Pinot and AWS Aurora PostgreSQL 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 Apache Pinot and AWS Aurora PostgreSQL records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Apache Pinot and AWS Aurora PostgreSQL connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Apache Pinot–AWS Aurora PostgreSQL integration in-house.
Yes — Stacksync ships production-grade connectors for both Apache Pinot and AWS Aurora PostgreSQL. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Apache Pinot: Not applicable for reads out (polling by time column); data enters Pinot via streaming ingestion or segment upload, not row-level writes. On AWS Aurora PostgreSQL: Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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 386 integrations available for Apache Pinot and AWS Aurora PostgreSQL.