DBConvert Streams vs Debezium: CDC Without the Kafka Stack

DBConvert Streams is a direct database-to-database CDC and migration tool with an embedded broker and a built-in IDE.

Debezium is an open-source CDC engine that captures database changes as Kafka events.

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MySQL → PostgreSQL · insert, update, and delete replicated live, both ends on screen

Quick answer

Choose by job

Choose DBConvert Streams if

  • Your goal is replicating data into a target database, not publishing events into Kafka.
  • Operating a Kafka cluster just for CDC is overhead you would rather avoid.
  • Your stack centers on MySQL/MariaDB, PostgreSQL, Snowflake, files, or S3.
  • You want initial Load, CDC, and validation inside the same product.

Choose Debezium if

  • Your stack already runs Apache Kafka and database changes need to flow into existing consumers.
  • You build event-driven systems where DB changes fan out to many downstream services.
  • You need broad source coverage including Oracle, SQL Server, MongoDB, Cassandra, or Db2.
  • You want a battle-tested OSS engine with a large community.

At a glance

Side-by-side facts

Aspect
DBConvert Streams
Debezium
Tool type
Database IDE + migration + CDC
Open-source CDC engine (Kafka Connect-based)
Output model
Direct write to target database, files, or S3
Change events into Kafka topics
Infrastructure
Self-contained desktop app or Docker distribution (NATS bundled — no external broker)
Kafka cluster + Kafka Connect + sink connectors + Schema Registry
Source coverage
MySQL/MariaDB, PostgreSQL, files, S3
MySQL, PostgreSQL, MongoDB, SQL Server, Oracle, Db2, Cassandra
Target delivery
Built-in: databases, files, S3
Sink connector required (Kafka → JDBC, S3, ES, etc.)
Initial snapshot + CDC in one tool
Yes (Load + CDC + Compare)
Partial (snapshot exists, no validation UI)
Built-in IDE / SQL editor
Yes
No
Source/target data comparison
Yes
No (consumer responsibility)
Files and S3 as targets
First-class (CSV, JSONL, Parquet)
Via Kafka Connect S3 sink
License
Free IDE + commercial Streams
Apache 2.0 (OSS)
Pricing model
Per-seat — $49/mo or $399/yr; no usage metering
Free software — cost is the Kafka/Connect infrastructure and the engineers who run it

AI and MCP

The AI difference

DBConvert Streams

DBConvert applies AI to operating the data workflow itself: exploring sources, checking results, and investigating CDC state through a read-only agent surface.

Explore DBConvert AI and MCP

Debezium

Debezium has AI-oriented transformations that generate embeddings from CDC events and feed current operational data into vector and RAG systems.

What to know: This is CDC plumbing for AI applications, not an in-product assistant, an operational agent, or a documented Debezium MCP server.

Where DBConvert Streams goes further

Skip the Kafka stack entirely

NATS is bundled with the desktop app and Docker distribution. No Kafka cluster, no Kafka Connect, no sink connectors, no Schema Registry. The same Docker images can still run in Kubernetes if your platform uses it.

Land changes directly in the target database

CDC writes straight to MySQL/MariaDB, PostgreSQL, files, or S3 — no Kafka topic in the middle, no sink to configure to produce usable rows.

Run initial Load and ongoing CDC from one UI

Same workspace handles the initial snapshot, source/target comparison, and continuous replication. Debezium handles the change stream; snapshot and validation are separate work.

Inspect data inside the same product

Browse schemas, run SQL, edit rows, inspect ER diagrams alongside the CDC stream. Debezium has no UI.

Write CDC straight into files and S3

Parquet, CSV, and JSONL are real CDC target types — no Kafka Connect S3 sink to author and operate.

Lower the operational floor for direct replication

One desktop app or Docker distribution vs Kafka + Connect + Debezium plugins + sinks + Schema Registry + monitoring. The gap is large when Kafka is only there for CDC.

Where Debezium wins

Capture changes from Oracle, SQL Server, MongoDB, Cassandra, Db2

Source connector library covers engines DBConvert Streams does not. For Kafka-shaped CDC pipelines from those sources, Debezium is the canonical choice.

Note — For migration and sync across Oracle, SQL Server, Db2, and other supported relational engines without Kafka, DBConvert and DBConvert Studio provide a dedicated migration workflow.

Explore DBConvert migration tools

Land DB changes as Kafka events for downstream consumers

Change events go directly into Kafka topics — stream processors, event-driven services, and analytics consumers read them through the Kafka they already operate.

Run at high throughput with proven patterns

Used by major engineering teams. Published patterns for high-throughput, multi-datacenter, and fan-out scenarios.

Drop into an existing Kafka platform

If Kafka, Schema Registry, and Kafka Connect are already deployed, Debezium connectors slot in with minimal new infrastructure.

Use a permissive OSS license

Apache 2.0 — no vendor licensing decisions, no per-seat or per-row pricing.

See it on your own databases — self-hosted, free evaluation, no credit card.

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Workflow

Replicate database changes to a target database without standing up a Kafka stack

  1. 1Install DBConvert Streams as a self-contained desktop app or a Docker distribution — the broker is bundled, no Kafka cluster to provision.
  2. 2Connect the source and target databases in Data Explorer and inspect schemas side by side.
  3. 3Run a Load-mode stream first to populate the initial target state.
  4. 4Open the Compare tab to validate row counts and sample data on the target.
  5. 5Switch to CDC mode and watch source changes apply directly to the target — no Kafka topic in the middle, no sink connector to configure.

Debezium emits change events into Kafka and ends there. DBConvert Streams delivers those changes directly to the target database, with the broker embedded.

Also supported

The same workflow runs for other source/target combinations:

  • PostgreSQL → MySQL/MariaDB (reverse direction, Load + CDC)
  • MySQL/MariaDB ↔ MySQL/MariaDB (homogeneous replication)
  • PostgreSQL ↔ PostgreSQL (homogeneous replication)
  • MySQL/PostgreSQL → files (CSV, JSONL, Parquet)
  • MySQL/PostgreSQL → S3-compatible storage
  • Files / S3 → MySQL or PostgreSQL

FAQ

Frequently asked questions

Is DBConvert Streams a Debezium replacement?

It depends on what you do with the change events.

  • Debezium — Emits change events into Kafka. The rest of the pipeline (consumers, processors, sinks) is your responsibility.
  • DBConvert Streams — Delivers changes directly to a target database, files, or S3 — no Kafka topic in the middle, no sink to configure.

For event-driven architectures fanning DB changes into many services, Debezium is the right shape. For replicating data into a target, DBConvert Streams condenses the pipeline.

Compare the Debezium alternatives side by side

Does DBConvert Streams use Kafka under the hood?

No. It uses an embedded NATS broker.

  • DBConvert Streams — NATS is bundled with the binary and the Docker distribution. No external Kafka cluster, no Kafka Connect, no Schema Registry to operate. The same Docker image can still be deployed to Kubernetes if your platform uses it.
  • Debezium — Designed around Apache Kafka and Kafka Connect. Debezium Server can run without Kafka (sinks include Pulsar, Kinesis, Redis Streams, and since mid-2026 a JDBC sink), but you assemble and operate that configuration yourself.

Can Debezium replicate directly between databases?

Since mid-2026, yes: Debezium Server ships a JDBC sink that enables a Kafka-less Source DB → Debezium Server → Target DB pipeline. It is still framework configuration — you assemble the properties, type mapping, monitoring, and cutover procedure yourself. The mainline Kafka pattern remains Source DB → Debezium → Kafka → sink connector → Target DB. DBConvert Streams packages the direct DB-to-DB pipeline as a product: UI, automatic table creation, type mapping, compare views, and run history included.

Which supports more source databases?

Debezium, including engines DBConvert Streams does not cover.

  • Debezium — MySQL, PostgreSQL, MongoDB, SQL Server, Oracle, Db2, and Cassandra as first-party connectors (plus additional community connectors).
  • DBConvert Streams — MySQL/MariaDB, PostgreSQL, Snowflake, files, and S3. DBConvert and DBConvert Studio cover migrations across additional relational engines such as Oracle, SQL Server, and Db2.

How does setup complexity compare?

Different operational floors.

  • Debezium — Kafka cluster + Kafka Connect + Debezium connector plugins + sink connectors + Schema Registry + monitoring. Amortized in stacks that already run Kafka; heavy if Kafka is only for CDC.
  • DBConvert Streams — Self-contained desktop app or Docker distribution. Broker is bundled. The IDE, Load mode, and CDC are all in the same product.

For event-driven stacks with Kafka in place, Debezium overhead is reasonable. For direct replication, DBConvert Streams removes most of the stack.

When should I not use DBConvert Streams?

When the goal is to emit events into Kafka topics for event-driven services, when you need Oracle, SQL Server, MongoDB, or Cassandra source coverage, or when you already operate a Kafka + Connect platform. In those cases Debezium is a better fit.

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