📄️ Get Started
A Crash Course in Deephaven is your backpack guide through the world of real-time data analysis using the Deephaven data engine. This guide provides a broad - but clear and technically informative - overview of Deephaven’s capabilities. Let's 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. Think of Deephaven tables like you think of Pandas DataFrames, except they support real-time operations! The Deephaven table is the key abstraction that unites static and real-time data for a seamless, integrated experience. This section will discuss the conceptual building blocks of Deephaven tables before diving into some real code.
📄️ Create Tables
Static tables
📄️ Table Operations
Table operations are an integral component of DQL. You've already seen a couple: update and where. You can think of these as different transformations being applied to the data in the table. This section will outline some basic table operations that make up the backbones of the most common queries.
📄️ Query Strings
Deephaven query strings are the primary way of expressing commands directly to the Deephaven engine. They are responsible for translating the user's intention into compiled code that the engine can execute. These query strings can contain a mix of Java and Python code and are the entry point to a universe of powerful built-in tools and Python-Java interoperability.
📄️ 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 empowers you to visualize it seamlessly. Deephaven provides a native plotting suite for all your plotting needs.
📄️ Export Data
Deephaven supports writing data out to various formats, such as CSV and Parquet. Deephaven can also export real-time data to new streaming sources, such as Kafka streams.
📄️ Configure your Instance
This last section covers configuration details needed to take your Deephaven instance beyond the defaults.
📄️ Wrapping Up
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