# Features (/features)

In addition to the [features](https://vectorbt.dev/getting-started/features/) available in the open-source
version, VBT introduces many significant enhancements and optimizations in the following areas:

*   [Data](/features/data): Connect, cache, transform, combine, and stream local and remote market data
*   [Indicators](/features/indicators) (Recently added): Build, search, stream with stateful accumulators, parallelize, and visualize indicator and signal pipelines
*   [Backtesting](/features/backtesting) (Recently added): Model orders, signals, leverage, stops, limits, cash flows, and simulation callbacks
*   [Analytics](/features/analytics): Inspect trades, patterns, projections, benchmarks, and excursion metrics
*   [Optimization](/features/optimization): Explore parameter spaces with cross-validation, conditional grids, and portfolio optimizers
*   [Performance](/features/performance): Scale computation with chunking, caching, JIT compilation, and parallel execution
*   [Tooling](/features/tooling) (Recently added): Prepare time-series arrays, automate research with the CLI and tasks, and configure or serialize reusable objects
*   [AI](/features/ai): Search knowledge, call functions, reason over sources, and build AI-assisted workflows

!!! info
    To keep pages concise, only a selection of the most interesting features from each release is highlighted.
    Full release notes are available exclusively to subscribers. If you are on the private website,
    navigate to *Getting started* → *Release notes*.

    Tags indicate releases where features were introduced for the first time. Please note that most
    features are continuously updated, so the following examples are intended to be run with the
    **latest** version of VBT installed ✍️

    ```python title="Import required by code examples"
    from vectorbtpro import *  # (1)
    ```

    1.  To view what is imported, call `whats_imported()`.