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 in Deephaven can communicate with OMS infrastructure, minimizing the path from research to alpha.
Systems for ingesting, storing and disseminating data focus on throughput and efficiency.
The platform delivers machinery, operations and scalability relevant for today’s capital markets.
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.
At its core, Deephaven is a column-oriented database that relies on authoritative sources to produce ordered, immutable data in 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.
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.
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 integrate with Jupyter, R-Studio, IDEs, Git, and more, and then augments them with a few interfaces of its own.User experiences empower productivity.