Snowflake’s 2026 has been all about one idea: making your data usable by AI agents without losing governance. Summit 2026 (June, San Francisco) packed in more than 25 announcements, and the release notes have kept coming through September and October.
This post filters it down to what matters for data engineers. For each item you get what it does and whether it is generally available (GA) or still in preview.
At a glance
| Feature | Area | Status |
|---|---|---|
| Apache Iceberg v3 support | Open formats | GA |
| Snowflake Storage for Iceberg tables | Open formats | GA |
| Snowflake Openflow (managed NiFi-based ingestion) | Ingestion | GA |
| Snowflake Datastream (Kafka-compatible) | Ingestion | Preview |
| Snowflake Postgres | Databases | GA |
| Postgres data mirroring into Snowflake | Databases | GA (October 2026) |
| Dynamic table incremental refresh improvements | Pipelines | GA (September 2026) |
| dbt Projects on Snowflake: Slim CI, defer, recovery | Pipelines | GA |
| CoWork (was Snowflake Intelligence) and CoCo (was Cortex Code) | AI | GA |
| AI Agent Identity | Security | GA |
| Horizon Context | Governance | Preview |
| Semantic View Autopilot | Semantics | Public preview |
1. Open formats: Iceberg v3 and one copy of your data
Iceberg keeps getting more central to Snowflake’s strategy, and 2026 is when it became a serious default rather than an experiment.
- Iceberg v3 (GA): adds deletion vectors, row lineage, the VARIANT type and default column values, with full insert, update, delete and merge support.
- Snowflake Storage for Iceberg tables (GA): Snowflake manages the storage, but the table stays open Iceberg that other engines can read.
- Horizon Catalog as the default catalog: Horizon now runs Polaris underneath, so you no longer need to manage a separate Polaris deployment. If you followed my earlier Polaris and Horizon guide, this simplifies the setup.
- Iceberg REST catalog: lets engines such as Spark or DuckDB write to the same tables Snowflake queries.
What to do: for new lakehouse tables that other engines need to read, start with Snowflake-managed Iceberg rather than native tables plus an export job.
2. Ingestion: Openflow, Datastream and zero-copy
- Openflow (GA): a managed integration service built on Apache NiFi, with connectors for databases, SaaS apps and files. A “headless” mode lets you define flows as code.
- Datastream (preview): a managed, Kafka-compatible endpoint. Producers that already speak Kafka can write straight into Snowflake tables, including Iceberg tables, without running Kafka Connect.
- Zero-copy integrations: SAP and Workday integrations reached GA, joining Salesforce. Data is shared without copying it into Snowflake. That is simpler, but not automatically cheaper, so compare costs with a normal ingest.
- Database connectors: the Oracle connector is GA; BigQuery, MongoDB and Veeva connectors are in preview.
3. Snowflake Postgres and mirroring
Snowflake Postgres is GA: a managed PostgreSQL service inside Snowflake, with PrivateLink and customer-managed keys for Business Critical accounts. In October 2026, Postgres data mirroring went GA on AWS and Azure. It continuously replicates Postgres tables into Snowflake using change data capture.
This is a big deal for app teams. Your operational database and your analytics can live on one platform, with no hand-built CDC pipeline in between.
4. Pipelines: Dynamic Tables and dbt grow up
- Incremental refresh with non-deterministic aggregates (GA, September 2026): more dynamic tables can now refresh incrementally instead of falling back to full refreshes.
- Refresh continues after failover (GA): dynamic tables keep refreshing incrementally after a failover to another region.
- Frozen period: stop a dynamic table from refreshing data before a set timestamp, which is useful for backfills.
- dbt Projects on Snowflake: Slim CI, defer to production, failed-run recovery and concurrent execution are now GA, so you can run dbt natively without a separate orchestrator for many teams.
I cover Dynamic Tables in depth, with SQL, in my Dynamic Tables vs Streams & Tasks tutorial.
5. AI: CoWork, CoCo and Cortex
- Rebrands: Snowflake Intelligence is now CoWork, a business-user assistant. Cortex Code is now CoCo, a coding agent available in Snowsight, Workspaces and a VS Code-based desktop app.
- Cortex Sense: builds context for agents from query history, dashboards and metadata, so answers use your business definitions.
- Semantic views: Semantic View Autopilot (public preview) drafts and refines semantic views for you, and DEFINE SEMANTIC VIEW in DCM projects is GA.
- Cortex Agent code execution (GA, October 2026) and the Cortex Agent SDK (preview) let you build agents that run code against governed data.
- More models: Anthropic Claude models power much of Cortex, and newer OpenAI and xAI models are available through Cortex AI.
6. Governance, security and cost controls
- AI Agent Identity (GA): each agent gets its own identity, role-based access and audit trail, rather than borrowing a human user’s role.
- AI Security Posture Management (public preview): Trust Center monitoring for AI risks such as prompt injection and data exfiltration.
- Horizon Context (preview): collects and enriches metadata so agents and people get consistent definitions.
- Per-user AI quotas: cap AI spend per user per day, alongside budgets and cost governance for shared warehouses.
- Adaptive compute: aims to tune compute automatically. It targets performance, not lower bills, so keep watching your credits.
For the cost side in detail, see my Snowflake cost optimisation playbook.
Who is building on Snowflake?
Snowflake used Summit to highlight Thomson Reuters building an enterprise AI platform on Snowflake, and announced a five-year, roughly $6 billion infrastructure commitment with AWS, including 10 new AWS regions. In the ecosystem, dbt Labs and Fivetran announced their merger at the event, and Snowflake announced its intent to acquire Natoma, an MCP gateway company, to connect agents to business tools securely.
My checklist for this quarter
- Review dynamic tables that run full refreshes. Some may now qualify for incremental refresh.
- Try Postgres mirroring if you run hand-built CDC from Postgres.
- Pilot managed Iceberg for one table that another engine needs to read.
- Set per-user AI quotas and budgets before rolling CoWork out widely.
- Give agents their own identities instead of shared service users.
- Move dbt runs into dbt Projects on Snowflake if your orchestration is simple.
Statuses reflect Snowflake announcements and release notes up to mid-October 2026, and recap sources do not always agree. Always confirm against the official Snowflake release notes before planning production work around a preview feature.
