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Crate matchcore

Crate matchcore 

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Matchcore is a high-performance order book and price-time matching engine implemented as a single-threaded, deterministic, in-memory state machine.

It is designed for building low-latency trading systems, exchange simulators, and market-microstructure research tools.

The architecture follows principles popularized by the LMAX Architecture, prioritizing deterministic execution, minimal synchronization, and predictable performance.

§Features

  • Price-time priority matching engine
  • Deterministic state machine execution
  • Single-threaded design for minimal latency
  • Efficient in-memory order book
  • Support for advanced order types and flags (e.g., iceberg, pegged, time-in-force)
  • Designed for integration with event-driven trading systems
  • Clear command → outcome model for reproducible execution

§What’s New in v0.4

This release introduces price-conditional orders and a revamped cascading execution model, enabling richer order semantics and a scalable foundation for complex order interactions.

§Price-Conditional Orders

Adds a new order type that remains inactive until a price condition is satisfied.

  • Activated when the market price reaches a specified threshold:
    • At or above a trigger price
    • At or below a trigger price
  • On activation, submits a new order (market or limit) to the book
  • The activated order is treated as a fresh submission with new time priority

This abstraction supports:

  • Stop-loss orders
  • Take-profit orders

§Execution Model

  • Orders are stored in a price-conditional sub-book
  • Once triggered, they are moved into a ready queue
  • Execution is integrated with the matching engine via cascading

§Activation Strategy

Activation depends on whether a last-trade price exists:

§With last-trade price
  • Conditions are evaluated immediately on submit/amend
  • Orders that already satisfy the condition:
    • Bypass the book
    • Go directly into the ready queue
  • Remaining orders are organized by trigger price levels and activated via range scans (drain_levels)
§Without last-trade price
  • Conditions cannot be evaluated at submission time
  • All orders are placed into a single pre-trade level
  • On the first trade:
    • Orders are evaluated in time priority order
    • Triggered orders are drained via drain_pre_trade_level_at_price

§Cascading Execution Model

Introduces a deterministic mechanism to process dependent order activations.

After a primary order execution:

  1. Execute all ready price-conditional orders triggered by the last-trade price change
  2. Execute an eligible pegged taker order
  3. Repeat until no further orders can be executed

This ensures:

  • Deterministic and reproducible behavior
  • Correct ordering of dependent executions
  • Proper handling of chained activations (conditional → pegged → conditional)

§Architecture

The design is heavily inspired by the LMAX architecture, a model widely used in low-latency trading systems.

Core principles include:

  • Single-threaded state machine
  • Event-driven command processing
  • Deterministic execution
  • In-memory data structures

These design choices eliminate synchronization overhead while guaranteeing reproducible behavior.

§Single-threaded

For an order book of a single instrument, events must be processed strictly sequentially.

Each event mutates the state of the book and the result of one event directly affects the next. Parallelizing matching for the same instrument therefore provides no performance benefit while introducing locking, contention, and complexity.

Running the matching engine on a single thread provides several advantages:

  • No locks, contention, or synchronization overhead
  • Predictable latency
  • Simpler correctness guarantees

This does not mean the entire application must be single-threaded.

A typical architecture may look like:

Command Reader/Decoder → Ring Buffer → Matchcore Engine → Ring Buffer → Execution Outcome Encoder/Writer

Systems can scale horizontally by sharding instruments across multiple engine threads.

For example:

Thread 1 → BTC-USD order book
Thread 2 → ETH-USD order book
Thread 3 → SOL-USD order book

§Deterministic

Matchcore operates as a pure deterministic state machine.

Given:

  • The same initial state
  • The same sequence of commands

the engine will always produce exactly the same results.

This property enables:

  • Deterministic replay
  • Offline backtesting
  • Simulation environments
  • Auditability
  • Event-sourced architectures

Deterministic execution is particularly valuable for trading systems where correctness and reproducibility are critical.

§In-memory

All state is maintained entirely in memory.

The order book, price levels, and internal queues are optimized for fast access and minimal allocations.

This design provides:

  • Extremely low latency
  • Predictable performance
  • Efficient memory access patterns

Persistence and replication are expected to be handled outside the engine, typically through event logs and snapshots.

§Core Concepts

Matchcore processes commands and produces outcomes.

Command → Matchcore Engine → Outcome

Commands represent user intent:

  • Submit order
  • Amend order
  • Cancel order

Outcomes describe the result of execution:

  • Applied successfully
  • Rejected because the command is invalid or cannot be executed in the current state of the order book

Successfully applied commands may also produce:

  • Trades
  • Order state changes
  • Triggered orders

§Example

use matchcore::*;

let mut book = OrderBook::new("ETH/USD");

let outcome = book.execute(&Command {
    meta: CommandMeta {
        sequence_number: SequenceNumber(0),
        timestamp: Timestamp(1000),
    },
    kind: CommandKind::Submit(SubmitCmd {
        order: NewOrder::Limit(LimitOrder::new(
            Price(100),
            QuantityPolicy::Standard {
                quantity: Quantity(10),
            },
            OrderFlags::new(Side::Buy, false /* post_only */, TimeInForce::Gtc),
        )),
    }),
});

println!("{}", outcome);

More examples can be found in the examples directory.

§Supported Order Features

Matchcore supports the following order types and execution options.

§Types

  • Market Order: executes immediately against the best available liquidity; optionally supports market-to-limit behavior if not fully filled
  • Limit Order: executes at the specified price or better
  • Pegged Order: dynamically reprices based on a reference price (e.g., best bid/ask)
  • Price-Conditional Order: becomes active when the market price satisfies a specified condition (e.g., at or above a trigger price); a generic category that includes stop-loss and take-profit orders

§Flags

  • Post-Only: ensures the order adds liquidity only
  • Time-in-Force: defines order lifetime (e.g., GTC, IOC, FOK, GTD)

§Quantity Policies

  • Standard: fully visible quantity
  • Iceberg: partially visible quantity with hidden reserve that replenishes

§Peg References

  • Primary: pegs to the same-side best price (e.g., best bid for buy)
  • Market: pegs to the opposite-side best price (e.g., best ask for buy)
  • Mid-Price: pegs to the midpoint between best bid and best ask

§Performance

Benchmarks are run with Criterion.

Matchcore is designed for low-latency, single-threaded, deterministic execution.

Representative benchmark results measured on an Apple M4 using Rust stable are shown below.

To run the benchmarks in your environment, run make bench.

§Submit

§Single-order submit

BenchmarkTime (median)
Single standard order into a fresh book~104 ns
Single iceberg order into a fresh book~104 ns
Single post-only order into a fresh book~104 ns
Single good-till-date order into a fresh book~116 ns
Single pegged order into a fresh book~61 ns
Single price-conditional order into a fresh book~112 ns
Single inactive price-conditional stop-limit order~130 ns
Single active price-conditional stop-limit order~142 ns

§10k orders submit

BenchmarkTime (median)
10k standard orders into a fresh book~272.60 µs
10k iceberg orders into a fresh book~274.71 µs
10k post-only orders into a fresh book~272.47 µs
10k good-till-date orders into a fresh book~284.36 µs
10k pegged orders into a fresh book~252.08 µs
10k price-conditional orders into a fresh book~280.79 µs
10k inactive price-conditional stop-limit orders~264.40 µs
10k active price-conditional stop-limit orders~540.86 µs

§Amend

§Single-order amend

BenchmarkTime (median)
Single order in single-level book quantity decrease~775 ns
Single order in multi-level book quantity decrease~621 ns
Single order in single-level book quantity increase~814 ns
Single order in multi-level book quantity increase~665 ns
Single order in single-level book price update~809 ns
Single order in multi-level book price update~684 ns

§10k orders amend

BenchmarkTime (median)
10k orders in single-level book quantity decrease~188.42 µs
10k orders in multi-level book quantity decrease~160.43 µs
10k orders in single-level book quantity increase~211.50 µs
10k orders in multi-level book quantity increase~185.59 µs
10k orders in single-level book price update~261.89 µs
10k orders in multi-level book price update~251.40 µs

§Cancel

BenchmarkTime (median)
Single order in single-level book cancel~789 ns
Single order in multi-level book cancel~613 ns
10k orders in single-level book cancel~138.39 µs
10k orders in multi-level book cancel~121.09 µs

§Matching

§Single-level standard book

Match volumeTime (median)
1~475 ns
10~484 ns
100~669 ns
1000~1.71 µs
10000~10.63 µs

§Multi-level standard book

Match volumeTime (median)
1~586 ns
10~592 ns
100~781 ns
1000~1.90 µs
10000~11.33 µs

§Single-level iceberg book

Match volumeTime (median)
1~472 ns
10~556 ns
100~1.12 µs
1000~5.16 µs
10000~39.26 µs

§Multi-level iceberg book

Match volumeTime (median)
1~580 ns
10~666 ns
100~1.23 µs
1000~4.45 µs
10000~36.30 µs

§Mixed workload

BenchmarkTime (median)
Submit + amend + match + cancel~9.77 µs

§Notes

  • Benchmark results depend on CPU, compiler version, benchmark configuration, and system load.
  • These figures illustrate the general performance profile of the engine rather than serve as universal guarantees.
  • Full Criterion output includes confidence intervals and regression comparisons.

§Next Steps

§Additional Order Features

  • Stop orders
  • Last-trade peg reference

§Potential Performance Improvements

Currently, the order book stores price levels using BTreeMap<Price, LevelId> and Slab<PriceLevel>. This design provides:

  • O(log N) best-price lookup
  • O(log N) submit operations to locate the corresponding price level
  • O(1) amend operations (except when amending the order to a different price level)
  • O(1) cancel operations (except when cancelling the order removes the price level entirely)

where N is the number of price levels.

An alternative design is to store prices in Vec<(Price, LevelId)>, sorted by price from worst → best, which provides:

  • O(1) best-price lookup
  • O(N) insertion / deletion when creating or removing price levels

However, in real-world trading scenarios, most activity occurs near the best price, meaning the effective search distance is often small. This can make a linear scan competitive with tree-based structures for typical workloads.

Structs§

AmendCmd
Represents a command to amend an existing order
CancelCmd
Represents a command to cancel an existing order
Command
Represents a top-level command for all kinds of commands and orders
CommandEffects
Effects from the execution of a command
CommandMeta
Represents the common metadata for all command kinds
DepthStatistics
Represents the depth statistics of the order book
Level1
Represents the level 1 market data of the order book
Level2
Represents the level 1 market data of the order book
LevelEntries
Shared order tracking for a level
LimitBook
Limit order book that manages limit orders and price levels
LimitOrder
Generic limit order with various configuration options
LimitOrderPatch
Represents the patch to a limit order
MarketImpact
Represents the market impact analysis of a market order
MarketOrder
Market order that is executed immediately and does not reside in the order book
MatchResult
Result of a match operation
Notional
Represents a notional value (price * quantity)
OrderBook
Order book that manages all kinds of orders and levels
OrderFlags
Flags that are common to all order types
OrderFlagsPatch
Represents the patch to the flags of an order
OrderId
Represents an order ID
OrderOutcome
Outcome of the order execution
PegLevel
Peg level that manages the status of the orders with the same peg reference. It does not store the orders themselves, but only the time priority information of the orders.
PeggedBook
Pegged order book that manages pegged orders and peg levels
PeggedOrder
Pegged order that adjusts based on reference price
PeggedOrderPatch
Represents the patch to a pegged order
Price
Represents a price
PriceCondition
Represents the condition that must be met for a price-conditional order to be activated
PriceConditionalBook
Price-conditional order book that manages price-conditional orders
PriceConditionalOrder
Represents a price-conditional order
PriceConditionalOrderPatch
Represents the patch to a price-conditional order
PriceLevel
Price level that manages the status of the orders with the same price. It does not store the orders themselves, but only the time priority information of the orders.
Quantity
Represents a quantity
QueueEntry
Represents a time priority queue entry
RestingLimitOrder
Represents a limit order resting in the order book
RestingPeggedOrder
Represents a pegged order resting in the order book
RestingPriceConditionalOrder
Represents a resting price-conditional order
SequenceNumber
Represents a sequence number
SubmitCmd
Represents a command to submit a new order
Timestamp
Represents a timestamp The timestamp is expressed as a Unix timestamp (seconds since epoch).
Trade
A trade that was made during a match
TriggerPriceLevel
Trigger price level that manages the status of the orders with the same trigger price. It does not store the orders themselves, but only the time priority information of the orders.

Enums§

AmendPatch
Represents the patch to an existing order
CancelReason
Reason for the order cancellation
CommandError
Error that violates the invariants of a command
CommandFailure
Reason for the command execution failure
CommandKind
Represents the kind of command
CommandOutcome
Represents the outcome of a command execution
CommandReport
Report from the execution of a command
NewOrder
Represents a new order for all order types
OrderKind
Represents the kind of an order
PegReference
Reference price type for pegged orders
QuantityPolicy
Represents the quantity policy of an order
Side
Represents the side of an order
TimeInForce
Specifies how long an order remains active before it is executed or expires.
TriggerDirection
Direction of trigger evaluation relative to the trigger price
TriggerOrder
Represents the order to execute when the condition is met