Next Gen
Data Platform
Platform Architecture
Data is about action, which means automation. Deephaven customers use the platform’s battle-tested APIs to serve source and derivative data real-time to dependent apps across the organization. Algos built into Deephaven can communicate with OMS infrastructure, minimizing the path from research to alpha.
Data Management System
Systems for ingesting, storing and disseminating data focus on throughput and efficiency.
At its core, Deephaven is a column-oriented database that relies on authoritative sources to produce ordered, immutable data in an append-only fashion.
It is built to play with a broad range of data storage choices including on-prem clusters, NFS and/or cloud storage solutions. The data adapter is designed to maximize throughput, employing smart caching and chunk sizes that are friendly to storage/transport layers.
An abstraction layer presents a unified view of the columnar data, relieving users of concerns about the how and where of the storage. This allows users and code to seamlessly mesh local and remote data, as well as both in-memory and on-disk payloads.
Query & Compute Platform
The platform delivers machinery, operations, and scalability relevant to today’s capital markets.
Deephaven supports analysis using a variety of languages and commodity hardware. The platform enables scalable, parallelized workloads. Code goes to data, not vice versa. Deephaven’s native table operations make anyone a player.
The system is designed for high-performance time series analysis. Interact with data directly. Combine query operations with user-defined functions in the same process. Scale across workers in a horizontal map or pipeline.
Enjoy consistency by connecting Deephaven to enterprise applications.
Powerful UI & Suite of Integrated Tooling
Users can use Jupyter, R-Studio, and classic IDEs, but Deephaven also makes available powerful, proprietary capabilities for working with and consuming data and results.
Working with data and building apps must be easy and quick. Deephaven offers intuitive and well-featured console, notebook, and editor UIs. Its dashboards are legendary. It’s simple to spin up views and visualizations and share them with teammates.
Queries persist – meaning they’re running all the time – updating as data hits source nodes.
Deephaven integrates with Jupyter, R-Studio, IDEs, Git, and more, and then augments them with a few interfaces of its own. User experiences empower productivity.
Deephaven Enterprise is a collection of enterprise-ready tools and exclusive add-ons to Deephaven Community that helps your team scale up quickly and benefit from the mutualization of enhancement requests. Professional services are available if you’d like more hands on deck.
| Community Core | Enterprise Edition | |
|---|---|---|
| Query Engine | ||
| High-performance real-time incremental updates | ||
| Batch and streams via a single abstraction | ||
| Streams on streams | ||
| Expressive query language / table API | ||
| Joins, aggregations, filters, sharding, decoration | ||
| Python, Java, C++ “code to data” | ||
| Query Syntax Tree | ||
| Support for exhausting transactions | Soon | |
| GUI-triggered, on-demand parameterized queries | ||
| Data Source integrations | ||
| Machinery for custom ingestors | ||
| Apache Parquet | ||
| Apache Kafka | ||
| CSV and files | ||
| Apache Arrow and Flight | ||
| ODBC / JDBC | ||
| CDC | ||
| XML | Soon | |
| Solace | Soon | |
| Code-generation for bespoke loggers and tailers | ||
| Manual input tables | ||
| Deephaven persistent format | ||
| Data Sink Integrations | ||
| Kafka | ||
| Parquet | ||
| CSV and files | ||
| Arrow and Flight | ||
| ODBC / JDBC | ||
| Solace | Soon | |
| Simple Binary Encoding | Soon | |
| Deephaven persistent format | ||
| APIs | ||
| Client APIs to manipulate tables, receive deltas and snapshots | ||
| gRPC and Arrow Flight-based communication | ||
| Communication via proprietary connections | ||
| Java API | ||
| C++ API | ||
| Python API | ||
| C# API | ||
| JavaScript API | ||
| Framework | ||
| High-performance data ingestion and federation service | ||
| Internal proxy services and communication protocols | ||
| Query worker dispatcher and registry | ||
| Data validation and cleaning gear | ||
| IDE integrations | ||
| Python REPL | ||
| Java Groovy REPL | ||
| Rich table UI | ||
| Shareable web dashboards | ||
| Deephaven Notebooks | ||
| UI data input experiences and forms | ||
| “Persistent Query” infrastructure | ||
| Built-in application scheduler | ||
| Sophisticated access controls | ||
| Plug-In engineering | ||
| Git integration | ||
| Schema management | ||
| Config management | ||
| System runbooks | ||
| 3rd party experiences | ||
| Jupyter | ||
| Excel | ||
| R Studio (and DFs) | Soon | |
| System monitoring integrations (Nagio, Geneos, Datadogg, etc.) | ||
| Pricing | ||
| Free | Contact Sales |