Institutional trading infrastructure engineered for speed and control.
BitAzure builds the core of a trading venue: a deterministic matching engine, order management, a risk engine that sits in front of the book, a market data engine and the FIX, REST and WebSocket connectivity that institutions and market makers require.
- Price-time priority matching engine with deterministic replay
- Order management, pre-trade risk and position limits
- FIX, REST and WebSocket connectivity for clients and market makers
- Market data engine with order book and trade feeds
What is a crypto trading platform?
A crypto trading platform is the set of systems that accept orders, validate them against risk rules, match them in an order book, record the resulting trades in a ledger and publish market data to participants. Institutional platforms add FIX connectivity, liquidity management tooling and monitoring that makes every state transition auditable.
BitAzure designs and builds these systems for exchanges, brokers and proprietary trading firms. The core is a single-writer matching engine per instrument fed by a durable event log, surrounded by an order management system, a risk engine that checks every order before it reaches the book, a settlement ledger and a market data publisher.
We treat the platform as a chain of deterministic state machines. Every input is logged, every output can be reproduced from the log, and performance is measured continuously against targets set during design rather than asserted after the fact.
Trading platform development services
Components can be delivered as a complete venue or adopted individually to replace parts of an existing stack.
Matching Engine
- Price-time priority order book with limit, market, stop and post-only orders
- Time-in-force handling: GTC, IOC, FOK and GTD
- Self-trade prevention and iceberg orders
- Single-writer design with deterministic sequencing
- Snapshot and replay from the event log
Order Management System
- Order lifecycle state machine with idempotent submission
- Account, sub-account and API-key scoping
- Trade execution reports and fill routing
- Amendment, cancel-replace and mass cancel
- Audit trail for every state transition
Risk Engine
- Pre-trade checks: balance, exposure and position limits
- Price collars and fat-finger protection
- Rate limits per account and per venue
- Kill switches at account, instrument and venue level
- Post-trade reconciliation against the ledger
Market Data Engine
- Order book snapshots and incremental L2 and L3 updates
- Trade, ticker, candle and index feeds
- Sequence-numbered WebSocket streams with gap recovery
- Conflation for slow consumers
- Historical capture into ClickHouse
Connectivity
- FIX 4.4 and 5.0 order entry and drop copy
- REST and WebSocket APIs with signed requests
- Low-latency WebSocket infrastructure with sticky sessions
- Binary protocols for colocated participants as an option
- SDKs and sandbox environments for integrators
Liquidity & Operations
- Market-making infrastructure: quoting engine and inventory controls
- Liquidity management with external venue routing
- Fee schedules, rebates and maker/taker tiers
- Monitoring: latency histograms, book integrity checks and alerting
- Capacity testing with replayed, production-shaped load
Reference trading platform architecture
Orders arrive through FIX, REST and WebSocket gateways, pass through order management and the risk engine, and are matched in a single-writer engine. A sequenced event log feeds the ledger, the market data publisher and monitoring, so every downstream view is derived from the same source of truth.
Hover or focus a component to see its role in the architecture.
- Trading Clients (UI · algos · market makers): Web and mobile terminals, algorithmic clients and liquidity providers.
- FIX Gateway (Order entry · drop copy): FIX 4.4 / 5.0 sessions with sequence management and certification environment.
- REST / WS Gateway (Auth · rate limits): Signed requests, per-key rate limiting and sequence-numbered WebSocket streams.
- Order Management (Lifecycle · accounts): Idempotent order intake, state machine, sub-account scoping and execution reports.
- Risk Engine (Pre-trade checks): Balance, exposure, position and price-collar checks; kill switches per account and instrument.
- Matching Engine (Price-time priority): Single-writer in-memory book per instrument with deterministic sequencing.
- Event Log (Kafka · sequenced): Durable, ordered record of every order, amendment and fill used for replay and downstream consumers.
- Ledger & Settlement (PostgreSQL): Double-entry balances, fee accounting and reconciliation to custody.
- Market Data Publisher (L2 · trades · candles): Book deltas, trades and aggregates fanned out with gap recovery and conflation.
- Monitoring (Prometheus · Grafana): Latency percentiles, throughput, book integrity and alerting.
Access
- FIX 4.4 / 5.0
- REST & WebSocket
- Auth & rate limiting
Order flow
- Order management
- Pre-trade risk
- Matching engine
Books & data
- Event log
- Ledger & settlement
- Market data
Operations
- Monitoring & alerting
- Replay & audit
- Capacity testing
Who builds trading platforms with BitAzure
Centralised exchanges
Spot and margin venues that need their own matching, custody integration and market data.
Brokerages and OTC desks
Order routing to multiple venues with a client-facing OMS and consolidated positions.
Proprietary trading firms
Internal execution stack with FIX connectivity, risk limits and strategy integration.
Institutional platforms
Sub-accounts, permissions, drop copy and reporting for funds and treasury desks.
Tokenised asset venues
Order books for security tokens with transfer restrictions enforced at settlement.
White-label trading products
A core engine reused across brands with separate fee schedules and branding.
Why teams choose BitAzure for trading systems
Deterministic core
Sequenced inputs and replayable logs make behaviour reproducible and incidents diagnosable.
Measured performance
Latency and throughput targets are defined in design and tracked in CI and production.
Risk before matching
No order reaches the book without balance, exposure and price checks.
Integrator-ready
FIX, REST and WebSocket interfaces with the documentation and sandboxes market makers expect.
Operational visibility
Book integrity checks, latency histograms and alerting from the first deployment.
Modular delivery
Engines, gateways and ledger can be adopted together or replace parts of an existing stack.
Technologies we use for trading platforms
Rust
BackendMemory-safe, low-latency engines, on-chain programs and tooling.
C++
BackendUltra-low-latency components in matching and market-data paths.
Go
BackendConcurrent network services, relayers and infrastructure daemons.
Java / Kotlin
BackendJVM services for enterprise integration and banking-grade systems.
Kafka
DatabaseDurable event streaming between engines and services.
PostgreSQL
DatabaseTransactional ledgers, ledgers-of-record and analytical workloads.
Redis
DatabaseCaching, sessions, rate limiting, pub/sub and order-book snapshots.
ClickHouse
DatabaseColumnar analytics for trade history and market data.
Kubernetes
InfrastructureAutoscaling, rolling deployments and workload isolation.
AWS
InfrastructureEKS, RDS, KMS, CloudHSM and multi-region deployments.
Prometheus / Grafana
InfrastructureMetrics, dashboards and alerting for every service.
TypeScript
FrontendStrict typing across the entire stack, client to contracts tooling.
How we deliver trading platforms
Every engagement follows a documented, milestone-driven path from discovery to continuous development.
- 01
Requirements and target metrics
Instruments, order types, participant profiles and target latency and throughput are agreed and written down.
- 02
Engine and data design
Order book structures, sequencing, event schema and ledger model are specified with failure-mode analysis.
- 03
Core engine build
Matching, risk and OMS are developed with property-based tests and replay harnesses from the first sprint.
- 04
Connectivity and market data
FIX, REST and WebSocket gateways and the data publisher are built and certified with test clients.
- 05
Load and failover testing
Replayed and synthetic load, node failures and network partitions are exercised before launch.
- 06
Launch and tuning
Staged rollout by instrument, followed by performance tuning and feature development.
Security practices in trading platform engineering
Authenticated order entry
API-key signatures, FIX session credentials, IP allow-lists and replay protection.
Risk isolation
Risk checks run in an independent component that no gateway can bypass.
Ledger integrity
Double-entry accounting with periodic reconciliation to custody and on-chain balances.
Immutable audit trail
Every order, amendment and fill is retained in a sequenced log with tamper-evident storage.
Segregated environments
Production, staging and sandbox are isolated with separate keys and access controls.
Incident controls
Kill switches, cancel-on-disconnect and circuit breakers tested as part of every release.
We coordinate independent third-party audits on request and never claim an audit, certification or compliance status unless it has actually been obtained.
What to decide before building a trading platform
Build vs licence
Licensed engines launch faster; a custom engine pays off when order types, latency or economics are differentiators.
Consistency vs latency
Synchronous durability protects against loss; asynchronous replication is faster. The choice must be explicit.
Custody integration
Where balances are held and how deposits and withdrawals interact with the ledger shapes settlement design.
Fee and rebate model
Maker/taker tiers and rebates steer liquidity provider behaviour and must be configurable without code changes.
Regulatory requirements
Licensing may mandate surveillance, reporting and record-keeping that need to be designed in from the start.
Liquidity strategy
Internal market making, external routing or partnerships each carry different technical and commercial obligations.
Crypto Trading Platform questions
Latency depends on hardware, network path and durability settings. During design we set example architecture benchmarks, such as sub-millisecond internal matching for an in-memory engine, and then measure against them. We do not publish guaranteed figures.
Planning an institutional trading platform?
Share your instruments, participants and performance goals. We will respond with an engine architecture and a delivery roadmap.