Siren Federate is a high-performance technology designed to enable large-scale search utilising unique and patented data joins. By distributing queries intelligently across federated sources, Siren Federate minimizes redundancy, retrieves only relevant data and ensures exceptional performance without centralizing data. Siren Federate saves time, resources and cost for IT departments and enables organizations to achieve unparalleled information retrieval, data discovery and scalability.
Apollo.io, a leading B2B sales intelligence platform, faced significant challenges with their search functionality, particularly when dealing with their two core data models: contacts and accounts. The platform maintained a synchronization system where account information was replicated to contact records to enable faster querying. However, this approach began to show its limitations, especially when handling accounts with large numbers of contacts and frequently changing fields.
Siren Federate enables real-time joins of massive datasets by connecting directly to multiple data sources without centralizing them. Its distributed query engine optimizes performance by pushing processing to the original systems, using advanced cross-source joins, dynamic schema mapping, and parallel execution. This architecture minimizes data movement and latency, allowing seamless integration of structured, semi-structured, and unstructured data. With features like customizable data models and caching, Siren Federate delivers scalable, fast, and efficient analysis across disparate datasets, ideal for investigative and analytical use cases.
Siren Federate achieves exceptional scalability and performance through its distributed, federated architecture and intelligent query optimization. By connecting directly to multiple data sources rather than centralizing them, it eliminates the need for large-scale data duplication. The system pushes query execution down to the original data sources, reducing data movement and leveraging the processing power of each source. It employs parallel execution for distributing workloads across nodes, ensuring efficient resource utilization. Additionally, advanced indexing, dynamic schema mapping, and intelligent caching optimize data retrieval and reuse. These features enable Siren Federate to scale seamlessly while maintaining high-speed performance, even for complex, cross-source analytics.
Siren Federate seamlessly integrates with both new and existing clusters by connecting directly to their underlying data systems without requiring data duplication or restructuring.
Chief Operating Officer at Apollo.io
The impact on our customers was immediate. Our products are now faster. Customers can use Apollo products in even more precise ways to filter and target, allowing sales and marketing teams to have unparalleled results.
Co-Founder and Chief Scientific Officer of Siren
Siren Federate was designed to handle mission critical, large-scale searches and the Apollo performance validates our approach.
