The July release of CData Sync is live, and this one has a few changes that will make your day-to-day noticeably smoother.
Here's what's new in this release:
🟢 Kafka just got a lot easier to set up
If you have been putting off Kafka as a destination because of the Schema Registry requirement, that requirement is gone. JSON is now the default message format, and Schema Registry config only appears when your chosen format actually needs it.
You also get real control over topic mapping and partitioning: one topic per table, all tables to one topic, or a custom template using {schema} and {table} variables. Partitioning can be round-robin, by primary key, or by a column expression you define. If you run CDC jobs feeding Kafka consumers, this one is for you.
📊 See exactly what is happening while jobs run
No more staring at a spinner. Tasks now show a live records-affected count that updates in real time as data lands at the destination, with no page refresh needed.
We also added a new task status: when a task processes a large volume of data and only a part of it fails while the rest succeeds, the result used to collapse into a generic ERROR. It now surfaces as PARTIAL_SUCCESS, so you know exactly what happened. If you have retry configured, it kicks in automatically.
🔄 CDC improvements across four connectors
- SnapshotMode replaces the old SkipSnapshot boolean with three clear options: Incremental, Full, or Skip. These are available in both job settings and the Resync modal. The options are more expressive and easier to reason about. The old flag still works but is deprecated.
- SQL Server CDC now handles zero-downtime schema changes automatically. Previously, a source schema change meant manual job recreation to avoid data loss. Sync now detects the two-capture-instance pattern, drains the old instance, and transitions on its own.
- Db2 for i CDC now checks for stable unique indexes before falling back to RRN as the merge key. RRN changes after table reorganizations, which caused duplicates and missed deletes. A unique index prevents that.
- SAP HANA CDC regenerates triggers automatically when a schema change is detected. Before this fix, new columns would silently replicate as NULL until you manually recreated the task.
⚙️ Pipelines: parallel steps and variables
Two updates land for Pipelines in 26.3. Steps can now run in parallel, so independent tasks no longer have to wait on each other. You can also define pipeline variables and reference them across steps, which makes it practical to build reusable, parameterized pipelines instead of duplicating logic.
🗂️ Schema setup is one step simpler
Sync no longer requires destination schemas to exist before a job runs. At job creation, choose whether to preserve your source schema structure or consolidate into a single target schema. If the schema does not exist yet, Sync creates it for you.
🆕 New destination: Apache Doris
If your team uses Doris as an OLAP layer, you can now replicate data directly to it without routing through a MySQL-compatible workaround. The connector handles Doris-specific data types and SQL syntax natively.
⚡ Postgres destination: faster writes
If you replicate to PostgreSQL, your jobs are now faster. Sync uses PostgreSQL's native COPY statement instead of row-by-row inserts, which cuts write time significantly for large data sets. No configuration is needed; it applies automatically.
⬆️ Getting the update
CData Sync 26.3 is available now. For full release notes, visit the CData Sync documentation portal.
Existing customers: download the latest release and generate an updated license key through the CData Portal.
Evaluating Sync for the first time: start a free trial.
📖 If you have questions or need help with any of these changes, our support team is available.
