Summit Season Cheat Sheet: What Snowflake and Databricks Will Announce in June
Informed predictions for Snowflake Summit (June 2-5) and Data + AI Summit (June 15-18), and the signals that actually matter. 12 Snowflake predictions and 19 Databricks predictions, ranked by confidence.
TL;DR. Most Summit Announcements Are Predictable. The Signals That Matter Are Not on Keynote Slides.
The value is not in what they announce. It is in separating the signals from the marketing.
31 predictions ranked by confidence across both Summits. Snowflake goes first with Polaris governance federation, ecosystem partners, and Iceberg v3. Databricks responds with Unity Catalog Iceberg write GA, agent governance, and IPO-ready framing. The announcements themselves are predictable if you read the trajectory. This guide tells you exactly what to watch for beneath the keynote slides, so you walk into each Summit already knowing what matters and what is theater.
Post-Summit Scorecard (June 3, 2026)
Snowflake Summit 2026 is done. Every Snowflake prediction below has been scored with sources. 0 wrong. 77.4% directionally correct. Databricks predictions will be scored after June 15-18.
| # | Prediction | Score |
|---|---|---|
| 01 | Polaris Governance Federation GA | Partially Right |
| 02 | Polaris Partner Ecosystem (15-20+) | Partially Right |
| 03 | Iceberg v3 "Day 0" Support | Nailed It |
| 04 | Policy Exchange Standards to Open Body | Partially Right |
| 05 | Cortex AI Expansion (Agents + Fine-Tuning) | Nailed It |
| 06 | AI Governance via Polaris | Partially Right |
| 07 | SPCS GA with GPU | Nailed It |
| 08 | S3 Tables Integration | Too Early |
| 09 | Unity Catalog into Polaris | Partially Right |
| 10 | Notebooks with AI Coding | Exceeded |
| 11 | Streaming-Native (Kafka) | Nailed It |
| 12 | Pricing Simplification | Partially Right |
Snowflake Summit 2026 (June 2-5, San Francisco)
Snowflake goes first. Their narrative advantage this year is real: Apache Polaris graduated to a Top-Level Project in February, and the April governance portability announcement (Policy Exchange Standards, Governance Federation, Read Restriction APIs) gives them a genuinely differentiated story. They have two weeks of framing before Databricks gets to respond.
Near-Certain Announcements
The April 2026 preview was a deliberate pre-Summit teaser. Snowflake's pattern of announcing preview 2-3 months before Summit, then announcing GA at Summit, is well-established. Expect a live demo showing governance policies enforced across Snowflake, Spark, Trino, and at least one other engine reading from Polaris-managed tables. This is the headline announcement.
Snowflake announced Horizon Catalog powered by Polaris with bidirectional interoperability and the Iceberg REST Scan Plan API for cross-engine governance. But governance federation went to private preview, not GA. My signal check was right: closer to roadmap than production. [source]
Expect a "Polaris Partner Ecosystem" announcement with connectors and integrations for DuckDB, Dremio, Starburst/Trino, AWS Athena, Google BigQuery, and others. Snowflake will frame Polaris as the Switzerland of catalogs.
Snowflake announced zero-copy integrations with SAP, Salesforce, Workday, AVEVA, and IBM. 200 partners at Summit. But the partner list was enterprise application vendors, not engine vendors (DuckDB, Dremio, Starburst). Right about the ecosystem push, wrong about who was on stage. [source]
Iceberg v3 brings row-level lineage, deletion vectors, VARIANT type, geospatial types, and nanosecond timestamps. Snowflake will position themselves as having full v3 support on day one, ahead of competitors.
Iceberg v3 went GA on May 7, 2026, before Summit even started. Even more aggressive than "Day 0." Snowflake claimed "broadest feature support on the market." My signal check landed: read + Snowflake-native write, but external writes through Horizon Catalog are not supported yet. [source]
Snowflake will likely announce that Policy Exchange Standards are being contributed to the Apache Iceberg community or a new cross-vendor initiative. This is the "governance should be an open standard, not a vendor lock-in tool" move, a direct shot at Unity Catalog.
Policy Exchange Standards are still in "working on" status. The OSI (Open Semantic Interchange) spec reached v1.0 with 54 vendors, but that is the semantic layer, not governance policy exchange. My signal check nailed it: closer to press release than public spec repo. [source]
Strong Predictions
Cortex Agents (autonomous AI agents querying data, building visualizations, taking actions within Snowflake) and Cortex Fine-Tuning (fine-tune LLMs on enterprise data within Snowflake's security perimeter) were in preview through 2025. Expect both to GA.
Capabilities shipped under new names. Fine-tuning became Cortex Training. Agents expanded into CoCo (coding agent, 72.1% ADE-Bench) and CoWork (knowledge worker agent with Deep Research). Cortex Sense added a shared context layer. The agentic capabilities exceeded what was predicted. [source]
Snowflake needs to close the AI governance gap with Unity Catalog. Expect an announcement around model governance, AI output auditing, LLM guardrails, and compliance tracking, all tied to the Polaris governance layer.
Snowflake shipped Agent Identity (GA), AI Security Posture Management, prompt injection safeguards, and acquired Natoma for MCP governance. More comprehensive than expected. But implemented through Horizon Catalog (proprietary), not Apache Polaris (open). My signal check caught the right distinction: right about the "what," wrong about the "where." [source]
SPCS has been in extended preview. GA with NVIDIA GPU support (H100/H200) for model training and inference within Snowflake would make the compute story more competitive with Databricks.
Four new SPCS instance families went GA on May 5, 2026, including GPU_L40S (NVIDIA L40S, 48GB VRAM) and GPU_R6K (NVIDIA RTX PRO 6000, 96GB VRAM). Different GPU models than predicted (L40S/RTX PRO 6000 vs. H100/H200), but the capability shipped. [source]
Expect native support for reading S3 Tables as an external catalog source in Polaris/Snowflake. This turns AWS's boldest storage-layer move into an on-ramp rather than a threat, and lets Snowflake emphasize that S3 Tables lacks the governance layer that Polaris provides.
No specific S3 Tables integration announcement at Summit. Snowflake focused on Horizon Catalog + Polaris bidirectional access and Snowflake Storage for Apache Iceberg Tables instead.
Medium-Confidence Predictions
A feature that reads Unity Catalog metadata into Polaris, essentially making Databricks customers' catalogs portable. This would be the most aggressive competitive move of the Summit.
The capability exists: Snowflake supports catalog integration for Unity Catalog (reading Iceberg tables from Unity on Azure went GA in April 2026). But it was quietly shipped as part of general interoperability, not positioned as an aggressive competitive move. [source]
Notebooks supporting Python, SQL, Markdown with Cortex-powered code generation, collaborative editing, and Git integration.
I predicted a feature. Snowflake shipped a product category. CoCo is a full autonomous coding agent across desktop, mobile, Slack, VS Code, and Claude Code. 72.1% on ADE-Bench, beating Claude Code and Codex (65.1%). 7,100+ customers. Fastest product adoption in company history. [source]
Dynamic Tables improvements (sub-second latency), possibly a native Kafka-compatible streaming endpoint. Streaming has been Snowflake's gap relative to Databricks; expect investment here.
Snowflake announced Datastream: a fully managed Apache Kafka-compatible streaming service built natively into the platform. Existing Kafka producers connect with zero code changes. Medium confidence, exactly right. [source]
Especially for AI/ML workloads. Possibly a "Cortex credits" model that simplifies pricing for inference and fine-tuning.
Snowflake announced Adaptive Compute (GA soon), which eliminates warehouse t-shirt sizing by auto-determining optimal resources per query. Consumption simplification through architecture, not pricing model change. No "Cortex credits." [source]
The Meta-Narrative
Every announcement will reinforce one message: "Open governance wins. Your data, governed everywhere, intelligent everywhere, open everywhere." Polaris TLP graduation gives Snowflake the structural credibility to make this argument. The question is whether the implementation matches the aspiration.
Databricks Data + AI Summit runs June 15-18, 2026. The 19 predictions below will be scored after the event. Check back for the update.
Databricks Data + AI Summit 2026 (June 15-18, San Francisco)
Databricks goes second. Their advantage is different: operational maturity (10,000+ enterprises on Unity Catalog), the Tabular team (Iceberg creators in-house), and the AI governance lead. They also have a significant backdrop: a potential IPO at a $134 billion valuation with $5.4 billion annualized revenue growing 65% YoY. Every announcement will be framed for Wall Street as much as for developers.
The confirmed keynote speakers include Ali Ghodsi (CEO), Matei Zaharia (CTO, fresh off winning the 2026 ACM Prize in Computing), alongside Jensen Huang (NVIDIA), Fei-Fei Li (Stanford), and Dario Amodei (Anthropic).
Near-Certain Announcements
This is the single most predictable announcement. Iceberg read has been GA; write has been in Public Preview. Azure GA evidence already appeared in Snowflake documentation as of April 2026. Expect full cross-cloud GA at the summit.
Currently in Public Preview: native Iceberg tables in Unity Catalog (not Delta-with-UniForm). GA at the summit would be the proof point that Databricks is genuinely format-neutral, not just format-tolerant.
Iceberg v3 entered Public Preview on Databricks on April 9, 2026, just two months before the summit. Full GA in two months is aggressive, but expect either GA announcement or a firm GA date. The three headline v3 features: Row Lineage, Deletion Vectors, and VARIANT.
The MCP (Model Context Protocol) Servers tab (Beta), MCP in Marketplace (Public Preview), and the Supervisor Agent (Beta) were all announced in early 2026. The summit is the natural venue to GA these. MCP is the hottest protocol in the AI agent ecosystem, and Databricks is positioning Unity Catalog as the enterprise governance layer for MCP.
Lakebase (the PostgreSQL-based operational database for AI workloads) went GA on AWS in early 2026, is in public preview on Azure. The summit is the natural venue for Azure GA and GCP preview. This is important for the AI agent story: agents need operational data access, and Lakebase provides it within the Unity Catalog governance perimeter.
Strong Predictions
Expect a major new capability for agent observability: tracking every tool call, model invocation, and data access across agent chains with full lineage in Unity Catalog. The analyst prediction of "MLOps and LLMOps merging into governed loops" is likely the framing.
Databricks already federates with AWS Glue, Hive Metastore, and Snowflake Horizon. The elephant in the room is Polaris. With Polaris at Apache TLP, Databricks needs a story. Expect either direct Polaris federation or a generic "federate with any Iceberg REST catalog" capability.
Databricks One (simplified business user interface) and Genie (natural language analytics) will likely GA with an "agentic Genie" that autonomously routes questions, chains queries, and reasons across data sources.
Read from Microsoft OneLake through Unity Catalog (currently in public preview) moves to GA. Write support to OneLake enters public preview. Deepens the Microsoft partnership and the Azure enterprise story.
Natural language to pipeline definitions, automatic optimization suggestions, intelligent monitoring. This extends the "AI everywhere" narrative from analytics into data engineering.
Medium-Confidence Predictions
Databricks engineers are driving three Iceberg v4 proposals: adaptive metadata tree (single-file commits), relative path support, and a modernized statistics model. A keynote segment from Matei Zaharia or Reynold Xin on "the future of open table formats" with an Iceberg v4 timeline would let Databricks frame the convergence narrative on their terms.
UC OSS v0.5 is expected with Metric View support. A v1.0 at the summit would be symbolically important, signaling the open-source project is production-ready independent of Databricks commercial offering. This counters the "UC OSS is a second-class citizen" criticism.
Snowflake's April 2026 governance portability announcement forces a Databricks response. Watch for "portable governance" or "governance federation" language: the ability to export/import Unity Catalog RBAC policies in a standard format.
With Dario Amodei (Anthropic) speaking, expect at least a deep Anthropic partnership announcement. A DBRX-2 (multimodal MoE successor) is possible but Databricks has been more focused on the platform than proprietary model training.
At least 2-3 industry-specific packages (financial services, healthcare, retail/CPG) with pre-built data models, compliance templates, and AI agent configurations.
With the S-1 expected in H2 2026, Ali Ghodsi's keynote will emphasize: $5.4B ARR, 65% YoY growth, 10,000+ enterprises on Unity Catalog, and the total addressable market. Every announcement will reinforce the growth narrative. Matei Zaharia's ACM Prize adds credibility at the exact moment they need Wall Street's attention.
The Meta-Narrative
Every announcement will reinforce one message: "The format war is over. The catalog is the platform. The platform is AI-native." Unity Catalog as governance + semantics + AI control plane, with Iceberg as a first-class citizen, and the Tabular team driving the convergence future.
The Signals That Actually Matter (Both Summits)
Most Summit announcements are predictable and priced in. Here are the non-obvious signals that will actually tell you which way the catalog war is trending:
The announcements themselves are predictable. The signals in the implementation details are where the real story lives.
The Week Between (June 5-15)
The ten days between Snowflake Summit ending and Data + AI Summit starting will be the most revealing period. Watch for:
- Databricks' response blog posts to Snowflake's announcements (published within 48 hours of Summit ending)
- Analyst hot-takes comparing the two governance stories
- Community reactions on social media, particularly from engineers who have used both catalogs in production
- Partner announcements that overlap: companies appearing in both partner ecosystems will be the ones who believe the catalog war resolves through coexistence, not winner-take-all
Summary: What Each Company Must Prove
| Snowflake Must Prove | Databricks Must Prove | |
|---|---|---|
| Governance | Federation works in production, not slides | Governance is portable, not Databricks-specific |
| AI | Polaris can govern AI assets, not just tables | Agent governance is catalog-level, not runtime-level |
| Formats | Full Iceberg v3 read AND write | Iceberg managed tables are first-class, not second-class |
| Openness | Policy specs are public and implementable | Unity Catalog OSS is production-grade independently |
| Ecosystem | Third-party engines work with Polaris live | Unity Catalog federates with Polaris |
| Future | Governance portability is real engineering | Iceberg v4 convergence has a timeline |
Snowflake Summit 2026 is done. Of 12 Snowflake predictions: 4 nailed, 2 exceeded, 5 partially right, 1 too early, 0 wrong. The signal checks were more accurate than the predictions themselves.
Databricks Data + AI Summit is next (June 15-18). The remaining 19 predictions will be scored then. Asking the right question matters more than predicting the right answer.
Technology Reference
A quick reference for key technologies and announcements discussed in this post.
Catalogs
| Technology | What It Is | Link |
|---|---|---|
| Apache Polaris | Open-source Iceberg REST catalog (Apache TLP, Feb 2026). Vendor-neutral standard with governance federation. | polaris.apache.org |
| Unity Catalog | Databricks catalog. Multi-format, AI governance, Business Semantics. 10,000+ enterprises. | unitycatalog.io |
| Snowflake Horizon | Snowflake's proprietary governance catalog. Integrates with Polaris for portability. | snowflake.com |
Snowflake Technologies
| Technology | What It Is | Link |
|---|---|---|
| Cortex AI | Snowflake's AI platform. Includes Cortex Agents (autonomous AI), Cortex Fine-Tuning, and Snowflake Intelligence. | snowflake.com/cortex |
| Snowpark Container Services (SPCS) | Run custom containers (including GPU workloads) inside Snowflake's security perimeter. | docs.snowflake.com |
| Policy Exchange Standards | Snowflake's proposed open standard for governance portability across catalogs and engines. April 2026 announcement. | snowflake.com |
Databricks Technologies
| Technology | What It Is | Link |
|---|---|---|
| Lakebase | PostgreSQL-based operational database for AI workloads. GA on AWS (early 2026). Provides operational data access within the Unity Catalog governance perimeter. | databricks.com |
| Databricks One / Genie | Simplified business user interface with natural language analytics. Genie routes questions and chains queries autonomously. | databricks.com |
| LakeFlow | AI-assisted data pipeline building. Natural language to pipeline definitions. | databricks.com |
| MCP (Model Context Protocol) | Protocol for AI agents to access tools and data. Databricks positioning Unity Catalog as the MCP governance layer. | modelcontextprotocol.io |
| Photon | Databricks native vectorized query engine for accelerated performance on Delta and Iceberg tables. | databricks.com |
| Liquid Clustering | Databricks-specific table optimization that replaces static partitioning with dynamic, query-driven clustering. | databricks.com |
Formats and Standards
| Technology | What It Is | Link |
|---|---|---|
| Apache Iceberg v3 | Latest Iceberg version. Adds row-level lineage, deletion vectors, VARIANT type, geospatial types, nanosecond timestamps. | iceberg.apache.org |
| Iceberg REST Catalog API | Universal catalog interface spec adopted by Polaris, Unity, Glue, BigLake. | iceberg.apache.org/spec |
| Delta UniForm | Databricks feature exposing Delta tables as Iceberg metadata for cross-engine reads. | docs.databricks.com |
About the author
Nidhi Vichare is an enterprise AI and data executive, platform architect, and author of The Meaning Layer. She writes about enterprise AI strategy, data architecture, causal measurement, AI ROI, agentic systems, and modern leadership for senior data and AI leaders.