From commit to action.
Connect a source for its selected mode. Remac operates the data path and delivers committed changes in order and at least once to analytics, search, services, data lakes, and other downstream systems. Dedicated workers. Private connectivity. No connector stack for your team to deploy or babysit.
Moving data shouldn’t cost you a team.
Today the options are heavy, expensive, or fragile. Here’s what data teams are actually living with.
Nightly ETL makes dashboards work from yesterday’s data. Time-sensitive decisions arrive late.
Debezium runs on the JVM. Kafka Connect mode also adds Kafka and Connect workers. Other modes remove some infrastructure, but teams still operate a Java-based CDC path.
Some managed connectors use row-based or usage-based pricing. Costs then grow with data activity and volume.
PostgreSQL replication moves data between PostgreSQL systems. Teams still need other paths when the same data must reach brokers, object stores, search, or another database engine.
A scheduled backup cannot restore changes that happened after its recovery boundary. Continuous log archiving and replay create a finer recovery path.
Scheduled re-index jobs leave search behind the source between runs. Users can then miss items that already exist.
Six capabilities. Two modes.
The industry often provides these functions through separate tools. They share one foundation. Logical functions use a decoded event path. Physical recovery preserves native log records and a compatible base snapshot.
Parse the log into ordered, row-level events. CDC, replication, heterogeneous sync, audit, and logical PITR share one decoded stream and one execution path.
Archive files or continuously stream raw log bytes for full-cluster recovery. The selected method determines the recovery point. No broker in the path.
One pipeline, a dozen jobs it retires.
Replace scheduled extraction with a continuous feed of selected committed changes.
Send selected changes to search as they commit instead of waiting for a full re-index.
One source, many sinks, in order. Replace N polling integrations.
Preserve selected committed changes and their available source context in an append-oriented record.
Write continuous JSONL to S3 and replace dedicated ingestion jobs where the pattern fits.
Tie embedding updates to selected committed changes instead of a full scheduled re-index.
Converge selected row state in PostgreSQL or map it to a different database engine such as MySQL.
Restore a compatible full cluster from physical records, or reconstruct selected logical state from archived events.
Replay archived normalized events through configured sinks to rebuild, repair, test, or reconstruct declared state.
“Every line of production code exists to move data from point A to point B without silent loss, broken order, or lost transaction context.”
“Trust comes from reliability. Reliability comes from testing. A rigorous test suite is not overhead. It is part of the product.”
“We handle other people’s data. A pipeline that silently drops events is worse than no pipeline because the operator believes replication is happening.”
“Six capabilities. Two underlying modes. One managed engine. We built one system around the full value of the transaction log.”
“The question is not only whether the pipeline works in normal conditions. It is what the pipeline does when its parts fail.”
“Every line of production code exists to move data from point A to point B without silent loss, broken order, or lost transaction context.”
“Trust comes from reliability. Reliability comes from testing. A rigorous test suite is not overhead. It is part of the product.”
“We handle other people’s data. A pipeline that silently drops events is worse than no pipeline because the operator believes replication is happening.”
“Six capabilities. Two underlying modes. One managed engine. We built one system around the full value of the transaction log.”
“The question is not only whether the pipeline works in normal conditions. It is what the pipeline does when its parts fail.”
One processor. Six transaction log functions.
Move committed data through one controlled path, with explicit ordering, delivery, and recovery boundaries.