Introducing Deephaven Enterprise 1.202601: Pivot tables, smarter queries, and a better developer experience
Powerful new tools for data exploration and streamlined workflows
March 30 2026
What if analyzing your data could feel as intuitive as thinking about it? With today's release of Deephaven Enterprise 1.202601, we're making that vision a reality — with pivot tables that reshape data on the fly, queries that automatically optimize themselves, and tools that let you debug without ever leaving your browser.
This isn't just an incremental update. Enterprise 1.202601 represents a fundamental shift in how you interact with your data.
Pivot tables, predicate pushdown, and in-browser debugging — Enterprise 1.202601 transforms how you explore and understand your data.
Pivot tables for interactive exploration
Enterprise 1.202601 introduces pivot tables — a new way to reshape and summarize data interactively without writing query code.
Create pivot views directly from any source table, drag and drop columns to reorganize your view, and apply filters and sorts interactively. The JavaScript API provides full pivot table support, making it easy to embed interactive pivot views in external applications.
Pivot tables are a display feature for exploring data. For programmatic data reshaping that produces tables you can use in downstream operations (joins, aggregations), use keyedTranspose.
Learn more about pivot tables →
Faster queries, automatically
Enterprise 1.202601 enhances predicate pushdown — the optimization that makes filtered queries dramatically faster. Data indexes can now accelerate most filter types, not just exact match lookups.
When you filter a table backed by Parquet, Deephaven leverages row group metadata and data indexes to skip reading unnecessary data. A query like:
This only reads the data that matches your filter instead of loading everything first. For large datasets, this can mean the difference between waiting minutes and getting results instantly.
This extends to where_in, where_not_in, and range filters — your analytical queries just got a whole lot snappier.
New tools for administrators
Enterprise 1.202601 adds tools that make administration easier:
Permission analyzer: The eternal question — "Why can't this user see this table?" — now has an instant answer. See exactly which ACLs apply, understand why access is granted or denied, and identify overly permissive rules, all from the UI.
Heap usage indicator: The console status bar now displays real-time heap memory usage for your worker. Spot memory issues before they cause failures.
Schema creation, simplified
The web-based schema editor now handles the entire data onboarding workflow:
- CSV import — Upload a file and let Deephaven auto-detect column types, preview data, and generate your schema.
- JDBC import — Connect to external databases, discover tables, and import schemas directly.
- XML editor with diff view — Edit schemas with syntax highlighting and see exactly what changed.
No more command-line tools. No more manual XML editing. Getting new data sources into Deephaven is now a visual, guided experience.
Build richer dashboards with deephaven.ui
The deephaven.ui component library expands with new tools for interactive applications:
| Component | What it does |
|---|---|
ui.toast | Show temporary notifications |
ui.menu | Create dropdown and context menus |
ui.color_picker | Let users select colors |
ui.accordion | Collapsible content sections |
ui.breadcrumbs | Navigation trails for hierarchical content |
ui.tag_group | Display and manage sets of tags |
ui.labeled_value | Display read-only values with labels |
Plus, dashboards now receive incremental updates instead of full refreshes — so complex UIs stay responsive even as data changes. You can also embed dashboards in external applications via iframe with proper authentication, and use ui.resolve to reference widgets from other Persistent Queries.
Iceberg integration
Enterprise 1.202601 adds native support for Apache Iceberg, the open table format that's becoming the standard for data lakehouse architectures:
- Read from Iceberg tables with full partition pruning.
- Write to Iceberg tables with schema evolution support.
- Connect to your existing catalogs — AWS Glue, Hive Metastore, and more.
Kubernetes gets smarter resource management
For teams running Deephaven on Kubernetes, Enterprise 1.202601 brings meaningful operational improvements:
- CPU limits — Prevent any single query from monopolizing cluster resources.
- Better memory accounting — More accurate tracking of non-heap memory reduces unexpected terminations.
- TLS by default — All inter-worker communication is now encrypted.
- Faster startup — Configurable DNS delays reduce pod startup failures.
Simpler certificate management
Good news for most deployments: if your certificates come from a well-known public CA, clients can now use their system's built-in trust — no Deephaven-specific truststores required.
For private CAs, the new DH_CA_CERTIFICATE property lets you provide your root CA bundle, and the installer handles the rest.
Note
Heads up for existing deployments: Native installations now require one certificate per machine, and hostname verification has changed. See the certificate management docs for migration details.
Streamlined binary logging
If you're streaming data into Deephaven, the new V2 logger format simplifies your configuration. One schema block now generates everything you need — no more maintaining separate logger and listener definitions.
Important
If you have custom binary log formats, regenerate your loggers after upgrading.
Security and engine updates
Security: Grizzly+ includes updates to Jetty (12.1.5), gRPC (1.76.2), Protobuf, Commons Compress, Jackson, and other dependencies. Container images now run with restricted privileges by default on Kubernetes.
Rollups enhanced: Rollup tables now support updateView for calculated columns, constituent filtering, and double/float columns as rollup keys.
Before you upgrade
A few things to check:
NULL and NaN handling has changed. Sorting now places NULLs first and NaNs last. Aggregations ignore NULLs and propagate NaN appropriately. If your queries depend on specific sorting behavior for missing data, test them before upgrading.
Formulas are now stateless by default for better parallelization. If your queries depend on evaluation order, you may need to mark columns as serial.
Environment requirements: Java 17, Python 3.10+, and Ubuntu 22.04 or later for Legacy workers. Core+ workers support Python 3.9-3.13.
Get started
Enterprise 1.202601 is available now. Check out the detailed release notes for the complete list of changes, and visit our upgrade guide when you're ready.
Questions? Our Slack community is always here to help.