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Releases: hump-cdc/hump

Release list

v1.0.1

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@sergeyzwezdin sergeyzwezdin released this 25 Oct 01:00
Immutable release. Only release title and notes can be modified.
a26083b

Fixes

  • Fixed Docker image publishing in CI.

v1.0.0

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@sergeyzwezdin sergeyzwezdin released this 25 Oct 00:28
Immutable release. Only release title and notes can be modified.
a180741

Features

  • Captures inserts, updates, deletes and truncates from PostgreSQL 15+ with no database extensions required.
  • Works with partitioned tables and TimescaleDB hypertables.
  • Sinks:
    • Kafka, with TLS, SASL, partition keys and headers
    • NATS Core and NATS JetStream
    • RabbitMQ, with delivery confirmation and detection of unroutable messages
    • RabbitMQ Streams
    • HTTP webhooks, with a configurable URL, method, headers and body
  • Ships as a single lightweight binary that starts with one command.
  • Official multi-architecture Docker image, signed and published with a software bill of materials.
  • Configure it with a YAML file, inline config, command-line flags or environment variables.
  • Sets up replication on start, and a cleanup mode removes everything it created.
  • Configures tables for full change capture automatically. You can turn this off for any table, and Hump warns about tables that are missing the setup.
  • Events use a Debezium-compatible format by default.
  • Every topic, subject, routing key, header and payload can be templated, with a rich function library for strings, case conversion, conditions and JSON.
  • Templates can tell a value the database didn't send apart from a real empty value.
  • Reusable sink presets, several tables under one config entry, and a filter that picks which change types each sink receives.
  • Your application can attach context, such as trace IDs, to a transaction, and Hump adds it to every event from that transaction.
  • At-least-once delivery: a change counts as processed only after every sink has delivered it.
  • Each sink has its own retry policy (exponential or linear backoff) and failure policy (stop or skip).
  • Snapshots load existing rows into the same sinks:
    • consistent point-in-time data
    • up to 10 tables in parallel
    • an optional row filter per table
    • row estimates before the run starts
    • live changes are held during the run and delivered once it finishes
    • start, stop and watch progress per table and per sink
  • Built-in web console:
    • dashboard, flows, statistics and configuration view
    • live event stream with a sink filter you can share as a link
    • snapshot page with a filter editor that has syntax highlighting, column autocompletion and suggested filters
    • light and dark themes
  • Prometheus metrics, including replication lag and processing time, plus health probes.