Optimization Microservice

Reduce Spend by Streamlining Market Data Flow

Xignite Optimization Microservice is a cloud-native pricing and reference data cost optimization solution that enables the control of large reference datasets via intelligent caching, sophisticated entitlements and advanced analytics and reporting.



Reduce Operational Risk

Reduce operational risk to critical business systems and users.

Minimize Exchange Audit Risk

Minimize market data compliance risk with a full audit trail and the ability to entitle and control any type of market data (real-time, reference, etc.).

Streamline Data Access

Streamline data flow access across vendors and data types.

Reduce Data Latency

Gain operational efficiencies by reducing data processing latency.

Reduce Market Data Costs

Reduce your market data costs by 20-40% per year

Standardized Data Connectors

Xignite Microservices are vendor-agnostic and can bring transformative results to any data set you license or collect. Today we have standardized data connectors for the Optimization Microservice to leading vendors such as:


Xignite Optimization Microservice enables the caching of large reference datasets which can reduce what you spend on multiple requests of the same field.


  • Configurable Caching Engine

    Configurable caching engine supporting custom business rules and user requirements.

  • RESTful APIs

    Hyper-scalable RESTful APIs for integration directly into applications.

  • SFTP Emulation

    Proprietary vendor SFTP emulation and simple REST API endpoints.

  • Cost and Usage Analytics

    Comprehensive cost and usage analytics including invoice reconciliation, usage analysis, and automated allocations.

  • Flexible Entitlement Policies

    Flexible rule-based entitlement policies and role-based assignments applicable to all entitlement models (terminals, data feeds, snapshots, cloud APIs, on-demand, circuit breakers, etc.).

  • Machine Learning Optimization

    Optimization on data requests and caching through machine learning models.

Want to reduce your data bill by up to 40% this year?