Crate vortex

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§🌪️ Vortex

📚 Documentation | 📊 Performance Benchmarks

§Overview

Vortex is a next-generation columnar file format and toolkit designed for high-performance data processing. It is the fastest and most extensible format for building data systems backed by object storage. It provides:

⚡️ Blazing Fast Performance
- 200x faster random access reads (vs. modern Apache Parquet)
- 2-10x faster scans
- 2-10x faster writes
- Similar compression ratios
- Efficient support for wide tables with zero-copy/zero-parse metadata
🔧 Extensible Architecture
- Modeled after Apache DataFusion’s extensible approach
- Pluggable encoding system, type system, compression strategy, & layout strategy
- Zero-copy compatibility with Apache Arrow
🗳️ Open Source, Neutral Governance
- A Linux Foundation (LF AI & Data) Project
- Apache-2.0 Licensed
↔️ Integrations
- Arrow, DataFusion, DuckDB, Spark, Pandas, Polars, & more
- Apache Iceberg (coming soon)

🟢 Development Status: Library APIs may change from version to version, but we now consider the file format stable. From release 0.36.0, all future releases of Vortex should maintain backwards compatibility of the file format (i.e., be able to read files written by any earlier version >= 0.36.0).

§Key Features

§Core Capabilities

✨ Logical Types - Clean separation between logical schema and physical layout
🔄 Zero-Copy Arrow Integration - Seamless conversion to/from Apache Arrow arrays
🧩 Extensible Encodings - Pluggable physical layouts with built-in optimizations
📦 Cascading Compression - Support for nested encoding schemes
🚀 High-Performance Computing - Optimized compute kernels for encoded data
📊 Rich Statistics - Lazy-loaded summary statistics for optimization

§Technical Architecture

§Logical vs Physical Design

Vortex strictly separates logical and physical concerns:

Logical Layer: Defines data types and schema
Physical Layer: Handles encoding and storage implementation
Built-in Encodings: Compatible with Apache Arrow’s memory format
Extension Encodings: Optimized compression schemes (RLE, dictionary, etc.)

§Quick Start

§Installation

§Rust Crate

All features are exported through the main vortex crate.

cargo add vortex

§Python Package

uv add vortex-data

§Command Line UI (vx)

For browsing the structure of Vortex files, you can use the vx command-line tool.

# Install latest release
cargo install vortex-tui --locked

# Or build from source
cargo install --path vortex-tui --locked

# Usage
vx browse <file>

§Development Setup

§Prerequisites (macOS)

# Optional but recommended dependencies
brew install flatbuffers protobuf  # For .fbs and .proto files
brew install duckdb               # For benchmarks

# Install Rust toolchain
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
# or
brew install rustup

# Initialize submodules
git submodule update --init --recursive

# Setup dependencies with uv
uv sync --all-packages

§Performance Optimization

For optimal performance, we suggest using MiMalloc:

#[global_allocator]
static GLOBAL_ALLOC: MiMalloc = MiMalloc;

§Project Information

§License

Licensed under the Apache License, Version 2.0.

§Governance

Vortex is an independent open-source project and not controlled by any single company. The Vortex Project is a sub-project of the Linux Foundation Projects. The governance model is documented in CONTRIBUTING.md and is subject to the terms of the Technical Charter.

§Contributing

See CONTRIBUTING.md for guidelines.

§Reporting Vulnerabilities

If you discovery a security vulnerability, please email vuln-report@vortex.dev.

§Trademarks

§Acknowledgments 🏆

The Vortex project benefits enormously from groundbreaking work from the academic & open-source communities.

§Research in Vortex

BtrBlocks - Efficient columnar compression
FastLanes - High-performance integer compression
FSST - Fast random access string compression
ALP - Adaptive lossless floating-point compression
Procella - YouTube’s unified data system
Anyblob - High-performance access to object storage
ClickHouse - Fast analytics for everyone

§Vortex in Research

Anyblox - A Framework for Self-Decoding Datasets

§Open Source Inspiration

§Thanks to all contributors who have shared their knowledge and code with the community! 🚀

Re-exports§

pub use vortex_file as file;
pub use vortex_buffer as buffer;
pub use vortex_dtype as dtype;
pub use vortex_error as error;
pub use vortex_expr as expr;
pub use vortex_flatbuffers as flatbuffers;
pub use vortex_ipc as ipc;
pub use vortex_layout as layout;
pub use vortex_mask as mask;
pub use vortex_metrics as metrics;
pub use vortex_proto as proto;
pub use vortex_scalar as scalar;
pub use vortex_scan as scan;
pub use vortex_utils as utils;

Modules§

accessor
aliases: Re-exports of third-party crates we use in macros exported from vortex-array.
arrays: All the built-in encoding schemes and arrays.
arrow: Utilities to work with Arrow data and types.
builders: Builders for Vortex arrays.
compress
compressor
compute: Compute kernels on top of Vortex Arrays.
data
display: Convert an array into a human-readable string representation.
encodings
iter: Iterator over slices of an array, and related utilities.
patches
search_sorted
serde
session
stats: Traits and utilities to compute and access array statistics.
stream
validity: Array validity and nullability behavior, used by arrays and compute functions.
variants: This module defines extension functionality specific to each Vortex DType.
vtable: This module contains the VTable definitions for a Vortex encoding.

Macros§

register_kernel: Register a kernel for a compute function. See each compute function for the correct type of kernel to register.
vtable

Structs§

ArrayAdapter: Adapter struct used to lift the VTable trait into an object-safe Array implementation.
EmptyMetadata: Empty array metadata
EncodingAdapter: Adapter struct used to lift the VTable trait into an object-safe Encoding implementation.
ProstMetadata: A utility wrapper for Prost metadata serialization.
RawMetadata: A utility wrapper for raw metadata serialization. This delegates the serialiation step to the arrays’ vtable.
VTableContext: A collection of encodings that can be addressed by a u16 positional index. This is used to map array encodings and layout encodings when reading from a file.
VTableRegistry: A registry of encodings that can be used to construct a context for serde.

Enums§

Canonical: An enum capturing the default uncompressed encodings for each Vortex type.

Traits§

Array: The public API trait for all Vortex arrays.
ArrayBufferVisitor
ArrayChildVisitor
ArrayVisitor
ArrayVisitorExt
DeserializeMetadata: Trait for deserializing Vortex metadata from a vector of unaligned bytes.
Encoding: Marker trait for array encodings with their associated Array type.
IntoArray: Trait for converting a type into a Vortex ArrayRef.
SerializeMetadata: Trait for serializing Vortex metadata to a vector of unaligned bytes.
ToCanonical: Trait for types that can be converted from an owned type into an owned array variant.

Type Aliases§

ArrayContext: A collection of array encodings.
ArrayRef: A reference counted pointer to a dynamic Array trait object.
ArrayRegistry
EncodingId: EncodingId is a globally unique name of the array’s encoding.
EncodingRef

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