A Crash Course in Deephaven

A crash course in Deephaven that covers the basics of working with tables and plots.

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Get started

This guide provides a broad - but clear and technically informative - overview of Deephaven’s capabilities. Dive in and unlock the potential of this powerful platform.

Architecture overview

Deephaven's power is largely due to the concept that everything is a table.

Create tables

Learn to create tables from scratch with synthetic data or by importing data from external sources.

Table operations

This section will cover some table operations that appear in almost all queries.

Query strings

Deephaven query strings are the primary way of expressing commands directly to the Deephaven engine. They translate the user's intention into compiled code that the engine can execute.

Python integrations

Deephaven empowers Python developers by providing efficient integrations with popular Python libraries. This section covers some highlights of Deephaven's Python interoperability as well as the inherent limitations of static Python data structures.

Real-time plots

Whether your data is static or updating in real time, Deephaven supports plotting via multiple libraries, including its own built-in plotting API.

Data I/O

Data I/O is mission-critical for any real-time data analysis platform. Deephaven supports a wide variety of data sources and formats, including CSV, Parquet, Kafka, and more.

Configure your Deephaven Instance

This section covers configuration details needed to take your Deephaven instance beyond the defaults.

Wrapping Up

Where to go from here.