A Debezium Alternative Without the Kafka Stack: DBConvert Streams vs Debezium

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

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

Try DBConvert Streams See the CDC workflow

Quick answer

Choose by job

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.

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, files, or S3.
You want initial Load, CDC, and validation inside the same product.

At a glance

Side-by-side facts

Aspect

Debezium

DBConvert Streams

Tool type

Open-source CDC engine (Kafka Connect-based)

Database IDE + migration + CDC

Output model

Change events into Kafka topics

Direct write to target database, files, or S3

Infrastructure

Kafka cluster + Kafka Connect + sink connectors + Schema Registry

Self-contained desktop app or Docker distribution (NATS bundled — no external broker)

Source coverage

MySQL, PostgreSQL, MongoDB, SQL Server, Oracle, Db2, Cassandra

MySQL/MariaDB, PostgreSQL, files, S3, Snowflake (coming soon)

Target delivery

Sink connector required (Kafka → JDBC, S3, ES, etc.)

Built-in: databases, files, S3

Initial snapshot + CDC in one tool

Partial (snapshot exists, no validation UI)

Yes (Load + CDC + Compare)

Built-in IDE / SQL editor

Yes

Source/target data comparison

No (consumer responsibility)

Yes

Files and S3 as targets

Via Kafka Connect S3 sink

First-class (CSV, JSONL, Parquet)

License

Apache 2.0 (OSS)

Free IDE + commercial Streams

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 MongoDB without Kafka, the broader DBConvert product line (DBConvert/DBSync and DBConvert Studio) covers it. Those are dedicated migration/sync tools — different shape from Debezium's event-stream model.

See the DBConvert product family

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.

Where DBConvert Streams wins

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.

Workflow

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

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

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, files, and S3 (Snowflake target coming soon). For Oracle, SQL Server, or Db2 migrations, see the broader DBConvert product line — DBConvert/DBSync or DBConvert Studio — covering 30+ engines and 400+ migration directions.