New and recent Databricks features to watch

What shipped in the last 90 days that I would raise with a client. Grouped by theme, not by date. I keep this list so I can answer "what changed?" without reading the whole feed, and so I can tell a client the difference between something they can build on and something they should only test.

Source is the official Databricks release notes. I do not add a feature that the notes do not name.

Conventions:

GA — generally available. Safe to design client work around.
Public Preview — usable and documented. Keep it off the critical path.
Beta — early. Test it, do not sell it.
announced — it appears in "What's coming". It is not usable yet. The date in parentheses is when Databricks announced it, plus the effective date when the notes give one.
(status: verify) — I could not pin the status. Check the live docs before you quote it.
Dates are the date the item appeared in the docs feed, in YYYY-MM-DD.
The feed is the AWS docs feed. Azure can lag, and some items are AWS-only. Confirm the Azure page before you give a client a date. I drop AWS-only items where I can identify them.

Data engineering and orchestration#

Declarative Automation Bundles default to the direct deployment engine — bundles deploy without the Terraform deployment engine. Bundles still on the Terraform engine migrate automatically. Status: announced (2026-06-03; effective 2026-07-24). Why it matters: this changes how every DABs deployment runs, and it is the first thing to check when a client's bundle deploy starts behaving differently.
Lakeflow Designer — a drag-and-drop canvas for preparing and transforming data. The output is production code governed by Unity Catalog. Status: GA (2026-06-16). Why it matters: gives analysts a supported path that does not end in an ungoverned notebook.
Unit testing for pipelines — write Python unit tests for Spark Declarative Pipelines in the Lakeflow Pipelines Editor, against mock data, with catalog-table redirection. Status: Beta (2026-07-26). Why it matters: pipeline tests were the weakest part of every CI story I have built. Watch this one.
Real-time mode in Spark Declarative Pipelines — end-to-end latency as low as five milliseconds for operational streaming. Status: Public Preview (2026-05-27). Why it matters: changes the answer when a client asks whether they need a separate streaming stack.
REPLACE WHERE flows — replace only the rows that match a predicate on each refresh, without reprocessing table history. Status: GA (2026-07-07). Why it matters: the standard fix for a full-refresh pipeline that costs too much.
REPLACE USING flows — for sources that arrive as partial snapshots keyed by column. Each update replaces the matching rows and leaves the rest. Status: Beta (2026-08-05). Why it matters: covers the snapshot-export pattern that many ERP and finance sources still use.
AUTO CDC flows for streaming tables in Databricks SQL — FLOW AUTO CDC on CREATE STREAMING TABLE, handling out-of-order records as SCD type 1 or type 2. Status: GA (2026-06-15). Why it matters: SCD2 without hand-written merge logic, from SQL.
Query-based connectors in Lakeflow Connect — ingest from a database with a cursor column, with no CDC configuration and no ingestion gateway. Status: GA (2026-05-29). Why it matters: removes the CDC prerequisite that blocks many first ingestion projects.
Microsoft Dynamics 365 connector — managed ingestion of CRM and ERP data through Azure Synapse Link. Status: GA (2026-06-26). Why it matters: an Azure-native path for the most common Microsoft-shop source.
SharePoint connector — ingest files and structured data from SharePoint sites. Status: GA (2026-08-04). Why it matters: pairs with the Excel and CSV sprawl that sits in every client tenant.
Lakeflow Connect row filtering — apply a WHERE-style condition during initial load and incremental sync. Status: GA (2026-07-02). Why it matters: cuts volume and duplication at the source instead of after landing.
MySQL integrated CDC pipeline — one pipeline for extraction and apply, without the gateway-based architecture. Status: Beta (2026-07-01). Why it matters: fewer moving parts than the gateway pattern, if it holds up.
Run a subset of job tasks with their dependencies — the + modifier runs a task with its upstream (+my_task), downstream (my_task+), or both. Status: GA (2026-06-30). Why it matters: makes partial reruns after a failure much less painful.
SQL alert task in Lakeflow Jobs — evaluate a Databricks SQL alert as a job task and branch downstream on the result. Status: GA (2026-06-29). Why it matters: puts a data-quality gate in the job graph instead of in a side channel.
Table update triggers on OpenSharing and system tables — trigger a job when a provider updates a shared table or when new rows land in a system table. Status: Beta (2026-06-03). Why it matters: event-driven operational jobs, such as reacting to a billing or audit table.
Behavior changes for continuous jobs and pipelines — configure a continuous schedule from the pipeline page, including job-level settings such as performance mode. Status: announced (2026-07-08; effective early Aug 2026). Why it matters: a configuration change that can alter the cost of an existing continuous pipeline.
Lakeflow Pipelines Editor becomes the default on compliance-profile workspaces — the legacy editor is removed at the same time. Status: announced (2026-07-09; effective Aug 2026). Why it matters: tell regulated clients before their team opens a pipeline and finds a new UI.

Storage and table formats#

Unity Catalog managed Apache Iceberg tables, foreign Iceberg tables, and Iceberg v3 — create and manage Iceberg tables in Unity Catalog, and read Iceberg tables that live elsewhere. Status: GA (2026-05-21). Why it matters: the format question is now a choice, not a lock-in argument. Expect it in every competitive evaluation.
Variant and Variant shredding — a data type for semi-structured data with structured-like query performance. Status: GA (2026-07-22). Why it matters: the right default for Event Hub and REST payloads, instead of a string column plus from_json.
Transactions across Unity Catalog managed Delta tables — group statements with BEGIN ATOMIC ... END or BEGIN TRANSACTION ... COMMIT. Status: GA (2026-07-22). Why it matters: removes a real objection from teams migrating from a relational warehouse.
Auto time-to-live (auto-TTL) — delete rows automatically from managed Delta tables, managed Iceberg tables, and streaming tables, based on a DATE or TIMESTAMP column. Status: GA (2026-06-12). Why it matters: a retention control that does not need a scheduled job. Useful in a data-protection conversation.
Convert a partitioned table to liquid clustering — ALTER TABLE ... REPLACE PARTITIONED BY WITH CLUSTER BY, with minimal reader and writer downtime. Status: GA (2026-06-12). Why it matters: the migration path for every over-partitioned legacy table you inherit.
Automatic upgrades roll out row tracking and Checkpoint V2 to existing tables — the rollout applies to existing Unity Catalog managed tables, not only new ones, and is gradual. Status: announced (2026-07-29). Why it matters: a table property changes on tables nobody touched. Know about it before a client's external reader complains.
Parquet v2 for Delta Lake tables — advanced encodings, v2 page headers, and INT64 timestamps, set with the delta.parquet.format.version table property. Status: GA (2026-06-29, Databricks Runtime 18.1 and above). Why it matters: smaller tables and faster reads, but it is opt-in and it affects external readers.
Configurable recovery period for dropped managed tables — set UNDROP recovery to 0 hours or to between 7 and 30 days. Default stays 7 days. Status: Public Preview (2026-06-15). Why it matters: answers the "prove the data is gone" question in a data-deletion policy.
Managed Iceberg materialized views — a materialized view that external Iceberg readers can read. Requires account team enablement. Status: Public Preview (2026-07-07). Why it matters: serve gold to an outside engine without a copy.
External data access for pipeline streaming tables and materialized views — external Delta and Iceberg clients read pipeline-managed tables through the Unity Catalog and Iceberg REST APIs. Status: Public Preview (2026-06-05). Why it matters: same argument, one layer down.
Change data feed on materialized views — read a CDF from a materialized view created in a Lakeflow pipeline or in Databricks SQL. Status: Beta (2026-08-07, Databricks Runtime 18 LTS and above). Why it matters: replicate gold changes outward without rebuilding the whole view.
UNIQUE constraint support — informational UNIQUE constraints on Unity Catalog Delta tables. RELY enables join elimination and DISTINCT simplification on Photon. Status: Public Preview (2026-06-05). Why it matters: a real query-plan win for a modeled star schema.
Delta Sharing is now OpenSharing — a rename that follows the open-source release. Status: GA (2026-06-10). Why it matters: update the word in every deck and doc. The product is unchanged.

Governance and Unity Catalog#

Secrets in Unity Catalog — store and govern secrets as securable objects in the three-level catalog.schema.secret namespace. Status: GA (2026-08-03). Why it matters: this changes my standing advice on secret scopes. Secrets read inside a job can now sit under the same grants and audit as the data.
Unity AI Gateway — governance for enterprise AI: control which AI services teams use, route traffic across providers, and govern MCP servers. Status: GA (2026-08-04). Why it matters: the control plane a client needs before they let teams call models freely.
MANAGE no longer requires USE CATALOG or USE SCHEMA on the same object — MANAGE now behaves more like ownership. Status: GA (2026-08-03). Why it matters: a privilege-model change. Re-read any Terraform grant module that worked around the old rule.
Role-based access control (RBAC) — a user assumes a role and uses only that role's permissions for the session, instead of their accumulated permissions. Status: Public Preview (2026-07-22). Why it matters: the first credible answer to "how do we give an admin exclusive, time-boxed access?".
ABAC GRANT policies — dynamically grant Unity Catalog privileges to objects whose governed tags match a condition, instead of granting object by object. Status: Beta (2026-06-11). Why it matters: tag-driven grants scale where per-object grants do not. See best-practices/governance-pii-abac.md.
Cross-engine attribute-based access controls — external engines read Unity Catalog managed Delta and Iceberg tables with ABAC, row filters, and column masks enforced server-side. Status: Beta (2026-05-28). Why it matters: masking that survives the trip to an outside engine.
Tag automations — assign or remove governed tags on tables and volumes that match conditions you define. Status: Beta (2026-08-07). Why it matters: governed tags only work if they stay accurate. This is the missing half of a tag-based ABAC design.
Governed tags system table — system.tags.governed_tags holds a record for each governed tag key in the account. Status: Beta (2026-07-24). Why it matters: lets you audit tag coverage from SQL instead of from the UI.
Governance Hub — an account-level console view of data health and coverage, AI usage and spend, and cost drivers. Status: Beta (2026-07-22). Why it matters: a ready-made governance report for a steering committee.
External lineage — register assets outside Databricks, such as a Power BI dashboard or a MySQL source, so one lineage graph spans the full flow. Status: GA (2026-06-08). Why it matters: lineage that stops at the workspace boundary does not satisfy an auditor.
Discover page — a curated browsing experience over Unity Catalog assets, organized by domains and subdomains. Status: Public Preview (2026-06-22). Why it matters: gives a data product a front door that is not the catalog tree.
Access requests across the metastore — enable access requests at the metastore level and set a destination that catalogs and schemas inherit. Status: Public Preview (2026-06-22). Why it matters: one routing rule instead of a per-object setting.
Request for Access enabled by default for all workspaces — requests route to the owner of the Unity Catalog object by email. Status: announced (2026-07-14). Why it matters: object owners start receiving email. Set the destination before the change lands.
Refresh materialized views and streaming tables under ABAC — the pipeline owner or run-as identity no longer needs an exemption from an ABAC policy. Status: GA (2026-08-03). Why it matters: removes the exemption that used to punch a hole in an otherwise clean ABAC design.

Identity, networking, and security#

Automatic identity management with Microsoft Entra ID — sync users, service principals, and groups from Entra ID to Databricks without SCIM provisioning. Status: GA (2026-05-26). Why it matters: this is now the default identity design on Azure. Use SCIM only where AIM does not apply. See lessons-learned/platform-lessons.md.
Automatic identity management for Okta — the same, for Okta tenants. Status: GA (2026-07-03). Why it matters: covers the clients who run Okta in front of Entra ID.
Identity federation enabled by default for new workspaces — including workspaces not attached to a Unity Catalog metastore. Existing workspaces are unaffected. Status: GA (2026-06-09). Why it matters: new workspaces behave differently from the ones a client already has. Say so during a rollout.
Explicit entitlements when adding principals to workspaces — entitlements are granted explicitly instead of inherited from the users system group. Admins can opt in from 2026-06-15. Status: announced (2026-06-08). Why it matters: a client who relied on inheritance will find new users have no entitlements. Plan the group design first.
Email notifications for expiring service principal tokens — Databricks emails workspace admins when a service principal token is within seven days of expiry. Status: GA (2026-07-22). Why it matters: the failure mode this prevents is a silent production job outage.
Authenticate as a service principal using OAuth U2M — obtain tokens as the service principal's identity when you hold the Service Principal Manager role. Status: Beta (2026-05-20). Why it matters: lets an engineer reproduce a job's permissions without holding the secret.
Context-based ingress control for workspace public access — allow and deny rules that combine identity, network source, and request type. Status: GA (2026-07-21). Why it matters: a finer instrument than an IP access list, and it does not need Private Link.
Partner platform IPs in context-based ingress control — allowlist the IP ranges that Power BI, Tableau Cloud, and dbt platform use. Databricks maintains the lists. Status: Beta (2026-07-14). Why it matters: ends the hand-maintained Power BI IP list.
Serverless compute access control — govern who runs serverless workloads through two built-in objects: Default Interactive Compute and Default Automated Compute. Status: GA (2026-08-03). Why it matters: serverless previously escaped the cluster-policy story. Now it does not.
Block specific internet destinations in network policies — block destinations from serverless workloads through the network policies REST API, regardless of the network access mode. Status: Public Preview (2026-06-23). Why it matters: egress control for serverless, which is the gap a security team always finds.
Private Link for account-level resources — reach the account console privately through a private endpoint instead of the public internet. Status: Beta (2026-07-06). Why it matters: closes the last public leg in a fully private design. Confirm Azure availability before you promise it.
Inbound Private Link for performance-intensive services — covers Lakebase Autoscaling and Zerobus Ingest. Status: GA (2026-06-08). Why it matters: OLTP and push ingestion can now sit behind Private Link.
Custom URLs for the account — a single branded entry point such as acme.databricks.com. Status: Public Preview (2026-07-15). Why it matters: small, but it removes the workspace-URL confusion that plagues large tenants.
Microsoft Entra ID SSO for Power BI — configure Entra ID as the identity provider for SSO from Power BI to Databricks, through an account-level federation policy. Status: Public Preview (2026-05-20). Why it matters: the Azure BI chain finally uses one identity end to end.

Resilience, cost, and operations#

Managed disaster recovery — replicates Unity Catalog metadata, managed table data, and workspace assets to a secondary region, with a stable URL that survives failover. Status: Public Preview (2026-06-12). Why it matters: replaces the hand-built DR runbook that most clients never finish. Watch this closely.
Mission Critical workspace add-on — bundles managed disaster recovery with the existing Enhanced Security and Compliance capabilities at a single compute rate, enabled per workspace. Status: Public Preview (2026-06-12). Why it matters: a new SKU to price before a client asks.
Budgets, including budgets for Unity AI Gateway — spending thresholds, with per-user thresholds and overrides for requests managed through Unity AI Gateway. Status: GA (2026-07-06). Why it matters: the control that makes a self-service AI rollout defensible.
Automatic cost attribution for materialized views and streaming tables in Databricks SQL — refreshes inherit custom tags from the enclosing SQL warehouse and propagate them to system.billing.usage. Status: GA (2026-08-03). Why it matters: closes a known blind spot in showback. See best-practices/auditing-and-system-tables.md.
Standard performance mode for MV and ST refreshes in jobs — a refresh orchestrated by a SQL task now respects the job's Performance optimized setting, and consumes fewer DBUs when it is off. Status: GA (2026-07-06). Why it matters: a cost lever that costs nothing to pull.
Instance events and instance pools system tables — system.compute.instance_events and system.compute.instance_pools track state transitions and pool configuration history. Status: Public Preview (2026-05-21). Why it matters: the missing piece for explaining a cluster that will not start.
Legacy compute_preview system schema deprecated — use system.compute instead. Status: announced (2026-06-22). Why it matters: check every dashboard and alert that queries the old schema.
View warehouse activity details — color-coded annotations on the Running clusters chart that explain why a warehouse stays active. Status: GA (2026-07-13). Why it matters: answers "why is this warehouse still billing?" without a query.
Lakehouse Replay — replays a sample of read-only serverless workloads against upcoming runtime releases to catch regressions before they reach production. No setup required. Status: Beta (2026-06-10). Why it matters: removes the strongest argument against serverless, which is loss of version control.
Deferred compute policy enforcement for all-purpose compute — apply a policy update the next time the compute terminates or restarts, instead of restarting it now. Status: GA (2026-06-10). Why it matters: lets you tighten a policy without interrupting a running analyst.

Compute and runtime#

Databricks Runtime 19 — powered by Apache Spark 4.2.0. JDK 21 only; the JDK 17 fallback is removed. Arrow-optimized Python UDFs are on by default, which can change type coercion. Status: GA (2026-07-23). Why it matters: two behavior changes that break real code. Test the UDFs before you upgrade a client.
Databricks Runtime 18 moves to LTS — three years of stability and security fixes. Status: GA (2026-07-23). Why it matters: DBR 18 LTS is the version to standardize on in a cluster policy right now.
JAR tasks on serverless compute — run a Scala or Java JAR as a Lakeflow Job task on serverless. The JAR must match the serverless environment's Scala, JDK, and Databricks Connect versions. Status: GA (2026-08-05). Why it matters: removes the last common reason to keep a classic cluster for a JVM workload.
Databricks Container Services for standard compute — specify a Docker image on standard compute, Databricks Runtime 18.3 or later. Status: Beta (2026-05-19). Why it matters: custom containers without dropping to a single-user cluster.
Workspace admin setting for the serverless notebook execution timeout — set the default under Settings > Compute, instead of asking for a manual override. Status: GA (2026-05-27). Why it matters: the serverless analogue of the auto-termination default I always override.
Improved workspace file read and write performance — prefetching for reads on serverless and Databricks Runtime 18 and above, and asynchronous flushing for writes on classic compute at Databricks Runtime 17.1 and above. Status: GA (2026-06-16 and 2026-06-04). Why it matters: repos with many small files, and Git operations in the workspace, get noticeably faster.
Dedicated group clusters on compliance-profile workspaces — assign compute to a group with Dedicated access mode, so members share compute and still run languages securely. Status: announced (2026-07-24; effective Sept 2026). Why it matters: gives regulated clients a shared cluster option they do not have today.

SQL and analytics#

Lakehouse Real-Time (Lakehouse//RT) — a serverless SQL warehouse type for low-latency, high-concurrency reads, with sub-second queries against Unity Catalog tables. Status: Beta (2026-06-30). Why it matters: serving analytical data to an application, without a separate serving database.
Warehouse-level statement timeouts — set statement_timeout per warehouse through the Create or Update warehouse APIs. API-only. Status: Beta (2026-07-21). Why it matters: a runaway query cap you can vary by workload, instead of one workspace-wide value.
Metric view parameters — bind values at query time and serve many query variants from one definition. Status: Public Preview (2026-06-26). Why it matters: one metric view instead of a copy per region or per business unit.
Window measures on a numeric index column in metric views — offsets and trailing or leading ranges over a consecutive integer order column. Status: GA (2026-08-05). Why it matters: fiscal weeks and 4-4-5 periods, which no calendar-date function handles.
MATCH_RECOGNIZE — the SQL:2016 row pattern recognition clause. Enable the preview in workspace settings. Status: Beta (2026-06-30). Why it matters: sessionization and funnel logic in SQL rather than in PySpark.
Excel file format support by default — read and query .xls, .xlsx, and .xlsm with no external library. Status: GA (2026-07-07). Why it matters: every client has an Excel source somewhere in bronze.
Standalone pipeline materialized views support expectations — add CONSTRAINT ... EXPECT (...) to a materialized view created in Databricks SQL. Status: GA (2026-06-23). Why it matters: data quality checks for SQL-authored assets, not just pipelines.
Change the owner of standalone streaming tables and materialized views — ALTER STREAMING TABLE and ALTER MATERIALIZED VIEW with SET OWNER TO. Status: GA (2026-06-23). Why it matters: fixes the orphaned asset an analyst leaves behind when they change teams.
Refresh policies and EXPLAIN CREATE MATERIALIZED VIEW — control when a refresh is incremental or full, and see why a plan chose one. Status: GA (2026-05-27). Why it matters: the cost of a materialized view is decided by this setting.

AI/BI, Genie, and the Microsoft surface#

Genie renamed across the product — Genie is now Genie One, Genie Spaces are now Genie Agents, and Genie Code is the coding surface. Capabilities are unchanged. Status: GA (2026-06-09 and 2026-07-08). Why it matters: fix the names in every deck before a client does it for you.
Genie pricing moved to pay-as-you-go — 150 DBUs of free LLM usage per user per month, about $10.50 in US East. Genie One and Genie Agents usage is free through 2027-01-31, and budget controls do not apply during the promotion. Service principals are excluded. Genie Code is billed. Status: GA (2026-07-08, promotion extended 2026-08-03). Why it matters: a client will plan around "free" and then get a bill in February. Say the end date out loud.
Databricks Genie app in Microsoft Teams — ask data questions in a direct message or by mentioning the app in a channel. Status: Public Preview (2026-07-17). Why it matters: the fastest way to put governed data in front of a Microsoft-shop business user.
Genie One in Microsoft Excel — query governed data in natural language from the Databricks Excel Add-in and import results as native rows. Status: GA (2026-08-05). Why it matters: it meets finance users where they already work.
Write data from Microsoft Excel back to Databricks — create or overwrite a Unity Catalog table from the Excel Add-in. Status: GA (2026-06-04). Why it matters: raise the governance question early. This is a write path into the lakehouse from a spreadsheet.
Databricks connector for Microsoft Power Platform — plus OAuth authentication as an alternative to a personal access token. Status: GA (2026-06-23; OAuth 2026-06-15). Why it matters: Power Apps and Power Automate against governed data, without a long-lived PAT.
Connect Genie to Microsoft Copilot Cowork — through the Genie managed MCP server. Status: Beta (2026-06-16). Why it matters: worth watching if a client has already standardized on Copilot.
Import Power BI and Tableau files as AI/BI dashboards — Genie Code rebuilds the visualizations, reuses metric views, and creates dashboard relationships where it detects them. Status: Public Preview (2026-07-09). Why it matters: turns a BI migration estimate from weeks into a spike.
Agentic code converter — converts T-SQL, Snowflake, Redshift, Oracle, BigQuery, and Teradata SQL to ANSI SQL, validating syntax as it goes. Status: Beta (2026-07-16). Why it matters: directly relevant to the Synapse work in migrations/azure-synapse-to-databricks.md. Test it before you scope the next migration by hand.
Git folders for dashboards — version control an AI/BI dashboard in Git. Status: GA (2026-07-16). Why it matters: dashboards can finally follow the same promotion path as code.
Dashboard relationships — multi-fact data models scoped to a dashboard. Status: Public Preview (2026-07-01). Why it matters: removes a real gap against Power BI's model layer.

Mosaic AI and model serving#

ai_query — call any supported model from SQL or Python. Status: GA (2026-06-15). Why it matters: the general-purpose entry point. Everything else in this section builds on it.
ai_extract and ai_classify — extract structured data against a schema, with citations and confidence scores, and classify text against custom labels. Status: GA (2026-06-11). Why it matters: two very common client asks, now with no endpoint to manage.
ai_search — retrieve from one or more AI Search indexes with a natural-language query, generating and reranking searches across sources. Status: Beta (2026-08-07). Why it matters: RAG retrieval as a SQL function.
Vector Search is now AI Search — the rename comes with full-text indexes that need no vectors or embeddings. Status: GA (2026-06-01). Why it matters: keyword search without an embedding pipeline changes the cost of a simple search feature.
AI Search High QPS — set a target QPS on standard endpoints for high-throughput workloads. Status: GA (2026-07-15). Why it matters: makes search bars and recommendations viable on a standard endpoint.
MLflow trace storage in Unity Catalog — unlimited storage, OpenTelemetry format, access governed by Unity Catalog schema permissions. Databricks recommends it for production. Status: GA (2026-07-16). Why it matters: agent observability that an audit can accept.
Endpoint telemetry and faster inference tables for custom model serving — persist OpenTelemetry logs, traces, and metrics to Unity Catalog, and deliver request and response payloads to an inference table view within seconds. Status: GA (2026-06-11) and GA (2026-06-12). Why it matters: closes the monitoring gap on custom endpoints.
Model services in Unity Catalog — a securable that represents a governed LLM endpoint, defined once and shared across workspaces. Status: Beta (2026-06-29). Why it matters: the cleanest way to stop each team from wiring its own endpoint.
Foundation model Unity Catalog permissions — control which Databricks-hosted models the organization can use, through permissions on the system.ai schema. Requires account team enablement. Status: GA (2026-06-05). Why it matters: the model allowlist a security review will ask for.
AI Functions Unity Catalog permissions — restrict which task-specific AI Functions are available, independent of model access. Requires account team enablement. Status: Public Preview (2026-07-08). Why it matters: a narrower control than blocking the model outright.
Managed agent memory — long-term memory across conversations, stored in Unity Catalog memory stores and governed as securables. Status: Beta (2026-06-23). Why it matters: removes the bespoke memory store from every agent project.
Databricks-managed MCP connectors move under Unity AI Gateway — connectors for Genie One and Genie Code are now governed, access-controlled, and visible alongside other MCP servers. Status: Beta (2026-08-06). Why it matters: MCP stops being a shadow integration path.
Model retirements — Google Gemini 2.5 Flash and 2.5 Pro retire on 2026-10-02. Anthropic Claude Sonnet 4 retires on 2026-10-09. Google Gemini 3 Pro is already retired. Status: announced (2026-07-08 and 2026-07-16). Why it matters: pin the model name in a client's code and put the retirement date in their calendar.

OLTP and apps#

Lakebase supports Postgres 18 — select it when you create a new project. Postgres 17 stays the default. Status: GA (2026-06-18). Why it matters: version parity matters when a team is migrating an existing Postgres application.
Customer-managed keys for Lakebase in all AWS and Azure regions — CMK encrypts Autoscaling project data at rest with a key in your own cloud KMS, for new projects. Status: GA (2026-05-20). Why it matters: Key Vault-backed encryption removes a common Azure blocker.
Lakebase snapshot storage is now billed — the size appears on the Backup & Restore page. Status: GA (2026-06-01). Why it matters: a live cost change on an existing deployment. Check a client's snapshot retention.
Postgres password authentication off by default for new Lakebase projects — existing projects are unaffected. Status: GA (2026-05-21). Why it matters: a connection string that worked in a proof of concept will fail in a new project.
Lakebase Autoscaling up to 64 CU (128 GB) — up from 32 CU. Status: GA (2026-05-20). Why it matters: raises the ceiling on what you can serve from Lakebase instead of from Azure Database for PostgreSQL.
Lakebase is SOC 2 Type 2 compliant — reports come from the account team. Status: GA (2026-07-14). Why it matters: the first question a client's security team asks about a new data store.
Databricks Apps horizontal scaling — run an app across multiple instances behind one URL, with zero-downtime deployment and session affinity. Status: Beta (2026-05-29). Why it matters: the availability story that makes Apps viable for something more than a demo.
Third-party apps from Databricks Marketplace — discover, install, and run partner apps in your own Unity Catalog-governed workspace. The provider's code stays closed. Status: GA (2026-06-16). Why it matters: a new procurement and review path a client's security team has not seen yet.
Databricks Apps on by default for compliance-profile workspaces — Status: announced (2026-07-31; effective early Sept 2026). Why it matters: regulated clients get a new capability they did not ask for. Decide the policy first.