DevReplicate
DevReplicate / Documentation
OPERATE WITH CONFIDENCE

Documentation

From the first replica to a developer-ready download: configure the engine you run, define what changes, and operate the enterprise controls without losing sight of the data boundary.

Core · Apache-2.0 Enterprise · Commercial license PostgreSQL · MySQL/MariaDB · Redis/Valkey MongoDB · Kafka · SQL Server · Oracle · CouchDB
WHY DEVREPLICATE

What it solves

Production-shaped development data, continuous replication, consistent joins and controlled delivery.

Explore the problems →
ADOPTION

Implementing it in your organization

Assign owners, write rules, validate an isolated replica and bring approved downloads into onboarding.

Plan your rollout →
CORE + ENTERPRISE

Pricing

Compare the free open-source core with Enterprise at 995 EUR per product licence per year.

Compare pricing →
CORE + ENTERPRISE

Set up each platform

Install with native packages or portable artifacts where available, build locally or in a container, then configure PostgreSQL/Patroni, MySQL/MariaDB/Percona, Redis/Valkey topologies, or one of the five newer engines.

Open setup guide →
CORE + ENTERPRISE

Configure anonymization

Choose transforms, map SQL columns, Redis values, document fields or Kafka record parts, reach nested JSON paths, and safely activate new policy with initial sync or backfill.

Open anonymization guide →
ENTERPRISE

API authentication & metrics

Configure RS256 verification, use scoped bearer tokens, manage fields or rules, trigger backfills, and connect Prometheus to the authenticated metrics endpoint.

Open enterprise API guide →
ENTERPRISE

Get the latest data

Publish verified replica artifacts and let developers retrieve, resume, verify, and restore them through shell scripts, Makefiles, or Docker-based workflows.

Open download guide →

The eight products

One product per engine family, one licence per product. The mechanism column explains how each product keeps a separate target current.

The DevReplicate family
Product Engines How it replicates
patroni-anonymizer PostgreSQL 13+ / Patroni Consistent baseline snapshot, then logical replication; the primary is discovered through Patroni’s REST API.
mysql-anonymizer MariaDB 10.11+, MySQL 8.0+, Percona Server 8.0+ Snapshot, then the row-based binary log.
redis-anonymizer Redis; Valkey 8.1+, including Valkey 9’s own RDB format Initial sync, then the replication protocol (REPLCONF/PSYNC); standalone, Sentinel or Cluster.
mongodb-anonymizer MongoDB 6.0+ replica set or sharded cluster Every collection copied once, then the deployment-wide change stream as an ordinary client; the resume token is checkpointed on the target.
kafka-anonymizer Apache Kafka 3.x (KRaft), Redpanda 24+ Each mirrored topic consumed and produced to the same-named target topic, same partition, key, headers and timestamp; the resume position lives in a compacted state topic on the target.
mssql-anonymizer Microsoft SQL Server 2019 / 2022, an edition with CDC Tables recreated and copied in primary-key order, then Change Data Capture polled from the recorded LSN and applied in commit order, checkpoint in the same target transaction.
oracle-anonymizer Oracle Database 19c, 21c, 23ai, 26ai Flashback copy AS OF SCN, then LogMiner over the online and archived redo; each committed transaction applied with its checkpoint in one target transaction.
couchdb-anonymizer CouchDB 3.x on both sides _all_docs for the first copy, then a continuous _changes feed with _bulk_get/_bulk_docs; _id and _rev preserved, checkpoint in _local/devreplicate-state.

Choose the correct edition

Core

Initial sync, continuous replication, configurable transforms, and backfill. Configuration is stored locally in SQLite.

Enterprise

Adds the authenticated reconfiguration API, Prometheus metrics, product-specific backup workflows, developer download endpoints and next-business-day support by e-mail.

Configuration defines the protection boundary. Unconfigured SQL columns and unconfigured document fields are copied unchanged, as are unmatched Redis keys unless the reject policy is on. Kafka is the exception in the other direction: a topic no rule matches is not mirrored at all unless you ask for passthrough. Review the complete dataset, complete any pending backfill or re-baseline, and verify the target before sharing it.