Airbyte vs DBConvert Streams
Airbyte is an open-source ELT platform that moves data from SaaS apps and databases into a data warehouse.
DBConvert Streams is a direct database-to-database migration and CDC tool with a built-in IDE.
Quick answer
Choose by job
Choose Airbyte if
- Your work is loading SaaS apps and databases into a data warehouse.
- Your destination is Snowflake, BigQuery, Redshift, or Databricks.
- Your team already operates an ELT pipeline stack and wants connector breadth.
- Scheduled batch sync is enough; sub-second replication is not part of the requirement.
Choose DBConvert Streams if
- Your work is moving and synchronizing operational data, not analytics ingestion.
- Real-time CDC is part of the requirement, not a connector-by-connector configuration.
- Your stack centers on MySQL/MariaDB, PostgreSQL, files, or S3.
- You want a self-hosted shape without standing up Kubernetes for it.
At a glance
Side-by-side facts
Where Airbyte wins
Load Salesforce, Stripe, HubSpot, and 300+ more sources
A connector library covering SaaS apps, databases, and event sources — the main reason teams pick Airbyte for analytics ingestion.
Land data in Snowflake, BigQuery, Redshift, or Databricks
Warehouse-shaped destinations with schema drift handling and incremental updates — the analytics targets most teams already use.
Fork, extend, or build connectors yourself
Open-source community plus the Airbyte Connector Development Kit. If a connector is missing, you can ship one.
Skip self-hosting with Airbyte Cloud
Managed Cloud option for teams that do not want to operate Kubernetes themselves.
Schedule pipelines and run dbt downstream
Pipeline scheduling, normalization, and downstream transformations via dbt — all inside the same ELT stack.
Where DBConvert Streams wins
Inspect data inside the same product that moves it
Browse schemas, run SQL, edit rows, inspect ER diagrams — alongside the replication. Airbyte assumes a separate SQL client.
Write directly to the target database, no warehouse hop
CDC and Load mode write straight to MySQL/MariaDB or PostgreSQL — useful for operational migration and homogeneous sync, not warehouse ingestion.
CDC happens as the source writes
MySQL binlog and PostgreSQL logical replication captured natively, with checkpointed state and resume. No Debezium-based connector to configure per database.
Validate the cutover with data, not just delivery
Compare row counts and sample content between source and target before turning on CDC. Airbyte ends in a warehouse; validation is the analytics layer's problem.
Read and write files and S3 like a database
CSV, JSONL, and Parquet are real source and target types — not just staging for warehouse loading.
Skip the Kubernetes floor
Self-contained desktop app or Docker distribution. The same Docker images can still run in Kubernetes if your platform uses it. Airbyte self-hosting effectively expects K8s.
Workflow
Replicate operational databases without routing them through a warehouse
- 1Connect source and target databases in Data Explorer and inspect schemas in the same UI.
- 2Run a Load-mode stream with table mapping and filters — data is written directly to the target, no warehouse hop.
- 3Open the Compare tab and verify row counts and sample rows on the target.
- 4Switch the stream to CDC mode to capture and apply ongoing source changes.
- 5Watch throughput, lag, and run history in Stream Monitor.
Airbyte would shape the same move as a connector-based pipeline into a warehouse. DBConvert Streams writes directly into the target database and keeps it in sync.
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 an Airbyte replacement?
No. They overlap a bit but target different jobs.
- Airbyte — Connector ELT for moving SaaS apps and databases into a data warehouse.
- DBConvert Streams — Operational database migration and CDC with a built-in IDE.
Teams ingesting Stripe or Salesforce into Snowflake pick Airbyte. Teams migrating or syncing MySQL/PostgreSQL pick DBConvert Streams.
Does DBConvert Streams support SaaS connectors like Airbyte?
No. DBConvert Streams focuses on databases, files, and S3-compatible storage as sources and targets. For SaaS-to-warehouse ingestion (Salesforce, Stripe, HubSpot, and similar), use Airbyte or Fivetran.
Which is better for direct database replication (MySQL, PostgreSQL, files, S3)?
DBConvert Streams, for most operational use cases.
- Airbyte — Can move data between databases but is shaped around warehouse pipelines; CDC support varies by connector and typically uses Debezium.
- DBConvert Streams — Native log-based CDC for MySQL and PostgreSQL, direct DB-to-DB write, source/target comparison in one UI — also between databases and files/S3.
Use Airbyte if the move is part of a larger warehouse pipeline. Use DBConvert Streams for direct operational replication.
Can I run DBConvert Streams without Kubernetes?
Yes. Kubernetes is optional, not required.
- DBConvert Streams — Ships as a self-contained desktop app (Windows/macOS/Linux) and as a Docker distribution. The same Docker images can be deployed to Kubernetes if your platform uses it.
- Airbyte — Self-hosting effectively expects Kubernetes.
Use whichever shape fits your stack — desktop, Docker distribution, or your existing Kubernetes cluster.
Does DBConvert Streams write to Snowflake, BigQuery, or Redshift?
Snowflake support is coming soon. BigQuery and Redshift are not currently targets. For warehouse ingestion today, Airbyte or Fivetran are better fits.
When should I not use DBConvert Streams?
When your job is SaaS-to-warehouse ingestion, you need 100+ connectors, or your destination is a cloud warehouse (BigQuery, Redshift, Databricks, or Snowflake before release). In those cases Airbyte or Fivetran are better fits.
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