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How Remac stacks up.

A direct technical comparison of deployment, operations, recovery, and architecture. Not a feature checklist.

Remac vs Debezium

JVM ecosystem
Infrastructure
Remac
Dedicated Remac Cloud. Remac operates the data plane, so your team does not run a JVM or Kafka Connect stack.
Debezium
Multiple deployment modes, all JVM-based. Kafka Connect mode needs a Kafka cluster, Connect workers, and JVM tuning. Every mode requires JVM operations and configuration.
Destinations
Remac
Writes directly to Kafka, S3-compatible storage, PostgreSQL, RabbitMQ, HTTP webhooks, and other approved destinations with native multi-sink fan-out.
Debezium
Debezium Server runs one source connector with one configured sink per instance. Direct fan-out needs multiple server instances or downstream infrastructure. Kafka Connect fan-out adds Kafka to the operating model.
Resource usage
Remac
Dedicated managed workers. Remac handles capacity, upgrades, and runtime tuning. Your team does not tune a JVM.
Debezium
JVM-based. Memory sizing, garbage collection, and JVM operations remain part of deployment and tuning.
Recovery
Remac
Managed physical and logical PITR plus REDO. Recovery uses declared retained state and confirmed positions.
Debezium
Stores connector offsets for capture resume. Replay depends on retained source or downstream data and separate operations. It does not combine CDC with physical and logical PITR and REDO.
Operating burden
Remac
No separate Remac CDC stack for your team to deploy, monitor, patch, or recover. Kafka remains optional as a destination.
Debezium
JVM tuning, monitoring, and infrastructure management regardless of deployment mode. Kafka Connect mode adds a full Kafka cluster to the operational surface.

Remac vs Fivetran

managed connector service
Latency
Remac
Real-time streaming from the transaction log directly to every configured sink.
Fivetran
Scheduled synchronization, not continuous transaction-log delivery. Even the fastest eligible one-minute schedule is periodic, and sync execution time adds to end-to-end lag.
Transaction-log scope
Remac
Remac is purpose-built for transaction log processing. One engine supports CDC, replication, audit logging, point-in-time recovery, and replay across logical and physical modes.
Fivetran
Fivetran uses transaction-log capture as one method for moving changed data through its connector and synchronization model.
Recovery
Remac
Managed physical and logical PITR plus REDO within the declared retained recovery window.
Fivetran
Connector recovery stays inside Fivetran's managed sync model. It is not an integrated physical and logical database PITR and REDO system.

Remac vs Airbyte

data movement platform
Focus
Remac
Purpose-built for transaction log processing. One engine for CDC, replication, audit, recovery, and replay.
Airbyte
A broad connector and data-movement platform with 600+ connectors. CDC is one capability within its sync-job model.
Latency
Remac
Remac processes committed changes in real time through a continuously operated transaction log data path.
Airbyte
Airbyte CDC runs inside scheduled or API-triggered sync jobs. Freshness depends on job frequency and execution time.
Recovery
Remac
Physical and logical PITR plus REDO. Recover declared work from retained safe positions without making full resynchronization the default.
Airbyte
Tracks the current log position between CDC syncs, but does not provide integrated physical and logical database PITR or REDO. Some schema and state changes still require refresh or reset operations.

Remac vs AWS DMS

cloud-locked
Portability
Remac
AWS-first managed service with provider-neutral engine and control-plane contracts. Remac is not defined by an AWS migration-task model.
AWS DMS
The DMS engine runs only in AWS. Your CDC pipeline logic, monitoring, and operations are locked to one cloud provider.
Configurability
Remac
Configure the managed pipeline through the hosted application, Cloud API, or Remac CLI. Remac handles the underlying runtime.
AWS DMS
Pipeline configuration and operations remain tied to AWS replication resources, task settings, mappings, metrics, and logs.
Multi-target
Remac
Native multi-sink fan-out from a single source stream. One replication slot, many destinations.
AWS DMS
One target per migration task. Fan-out means duplicating the entire task.
Recovery
Remac
Built-in physical and logical PITR plus REDO. Recover to selected points within the retained recovery window.
AWS DMS
Provides CDC recovery checkpoints for task resume or a new task start. It does not combine CDC with built-in physical and logical PITR and REDO.

Remac vs pglogical

PostgreSQL extension
Destination support
Remac
Kafka, S3-compatible storage, PostgreSQL, RabbitMQ, and HTTP webhooks. One source, many destinations.
pglogical
PostgreSQL-to-PostgreSQL only. No Kafka, no S3, no message queues. Fine until you need data anywhere else.
Fan-out
Remac
One-to-many fan-out from a single replication slot. No source overhead per destination.
pglogical
One-to-one replication. Each additional destination requires a separate replication slot on the source.
Transforms
Remac
Configurable pipeline with middlewares (filtering, transformation, etc). Deliver only the changes that matter to each sink.
pglogical
No transformation, no routing, no event-level processing. Publication-level row filters exist (PG 15+) but that's it. What the WAL produces is mostly what you get.
Recovery
Remac
Physical full-cluster recovery plus logical PITR and REDO through configured sinks.
pglogical
Limited to what PostgreSQL provides natively. No cross-engine PITR.

One processor. Six transaction log functions.

Move committed data through one controlled path, with explicit ordering, delivery, and recovery boundaries.

Read the fundamentals