Open table formats have become a foundational part of how modern analytics platforms are built. Teams want the flexibility of data lakes, but with the structure, governance, and auditability traditionally associated with warehouses.
Apache Iceberg has emerged as one of the leading answers to that problem.
With the v26 release, CData Sync now supports writing directly to Iceberg tables, giving teams a new way to land replicated data into governed, analytics-ready structures without giving up control.
This capability builds on Sync’s existing support for Delta tables and reinforces a consistent product direction: teams should be able to choose how their data is stored and governed, without changing how they ingest it.
Why Iceberg has become an open standard
Iceberg matters because it brings clarity to environments that are otherwise difficult to manage at scale, whether data is ultimately queried through a warehouse, a lakehouse, or both.
Schemas are explicit and evolve safely over time. Data changes are tracked through snapshots that support time travel and auditability. Writes are transactional, even on object storage.
For teams operating shared lakehouse or warehouse environments, the impact is straightforward. Analysts query consistent data. Engineers evolve schemas without breaking downstream consumers. Compliance and audit teams can reference historical table states directly.
By supporting Iceberg natively, Sync allows operational data to arrive in that governed state immediately, instead of relying on downstream tooling or custom logic to impose structure after the fact.
Delta or Iceberg: the choice is intentional
With Sync v26, Iceberg joins Delta as a first-class table format option. This is not a transitional step or a temporary bridge. It reflects how real organizations operate today.
Some teams standardize on Delta because of its tight alignment with specific platforms. Others prefer Iceberg for its engine-agnostic model and open governance. Many organizations use both, depending on workload, domain, or team ownership.
Many Snowflake customers are increasingly standardizing with Iceberg as their preferred open table format, particularly as they extend analytics beyond fully managed warehouse tables into lakehouse-style architectures. Iceberg allows Snowflake-centric teams to maintain governed, auditable tables while keeping data in open storage that can be accessed by multiple engines over time.
But Sync doesn’t force a single answer. The same replication jobs, change handling, and operational controls apply regardless of whether data lands in Delta or Iceberg tables. The difference is how that data is represented and governed once it reaches the lakehouse or warehouse.
That separation matters. It allows platform teams to set standards without constraining ingestion, and it allows data teams to adapt storage decisions over time without rebuilding pipelines.
Governed tables with clear behavior
One of the persistent frustrations with managed data ingestion tools is loss of visibility. Data arrives in a table, but how it was structured, versioned, or transformed along the way is difficult to inspect or explain.
Sync takes a more transparent approach.
When writing to Iceberg tables, Sync preserves explicit schemas, applies changes incrementally, and produces auditable data files aligned with Iceberg’s snapshot model. There are no proprietary wrappers or hidden normalization layers obscuring how data is laid out.
Teams can trace how data changes over time, understand the impact of schema evolution, and debug issues without reverse engineering vendor-specific behavior.
Part of a broader foundation
Apache Iceberg support is one part of the Sync v26 release. Alongside continued investment in Delta tables and other platform capabilities, it reflects a broader focus on choice, governance, and operational clarity across modern data pipelines.
For a full overview of what’s included in v26, or to learn more about when Delta or Iceberg is the right fit for your environment, see the v26 release overview and related Delta documentation.
