Our Matching Engine identifies music that has been streamed on digital and traditional services so artists get paid.
If you are a collective society facing increasing data volumes and changing file formats the Matching Engine can help you.
Built on modern cloud technologies it matches streaming music log files at a fraction of the cost and at multiple times the performance of legacy systems. It gives you the confidence to tackle streaming data with higher accuracy and operational costs you control.
We understand very high performance is needed to process streaming data. The Matching Engine supports Horizontal scaling as standard. The design is cloud native and optimised for Azure Service scaling. We have production environments autoscaling to 30,000 work matches per minute and our tests indicate we can scale to multiples of this.
Matching configuration parameters are conveniently organised in a three-level hierarchy and can be configured differently at each level. The Engine uses the hierarchy to identify the correct configuration setting for a given source or metadata characteristic. For example, a general work title similarity percentage could be defined and an alternate work title similarity percentage that applies to all publisher sourced matching could also be defined.
The Matching configuration parameters can easily be changed by business users and system administrators.
The “look ahead” scaling feature monitors data volumes and data types in the Ingestion Pipeline and automatically pre-scales to meet demand. Scaling and the cost of cloud resources are placed under your control.
Scaling rules can be configured by data source and be automatically invoked when the data type is detected in the Ingestion Pipeline.
Connection to on-premise and cloud repertoire and works databases is supported. Azure Data Factory is configured to manage the data extraction and loading to Azure storage for use by the Matching Engine. Azure Data Gateway is installed locally to your existing repertoire database, either on-premise or your cloud environment and configured to manage the extraction.
Built on a modern cloud architecture using Microsoft Azure – Storage, application components and integration services are all built on Azure PaaS services supporting auto-scaling and resilience.
Azure is available in over 140 countries world-wide – the Matching Engine can be installed in an Azure Data Centre near you.
As your data volumes change, the Matching Engine can scale to meet demand. Autoscaling takes advantage of the elasticity of the cloud while easing management overhead.
You can use our high performance Bulk Ingestion Pipeline to feed data into the Matching Engine.
This highly scalable ingestion and extraction engine manages the processing of batch-based messages and can be configured to provide batch responses.
Multilingual repertoire works data bases are supported as multi-character sets. Configuration rules and parameters can be adjusted for your language to optimise matching for common strings.
All the common log file formats are supported e.g. DSPs such as Spotify, Apple and YouTube. Additional formats can be easily configured.
You have a choice of setup and configuration options. We can provide documentation and training for your IT services team, or you can avail of our package service offering to quickly have the Matching Engine setup and configured to work with your data and log files.
The Matching Engine can be provided as a fully managed service with daily monitoring, regular health checks and full system administration. Alternatively, you can decide to have the Matching Engine managed by your existing IT services team. We provide a full set of configuration, system administration and run book documentation.
The Matching Engine is designed to be cost-effective. You pay for the Matching Engine monthly and only for the cloud resources you consume.
