PERFORMANCE & sCALABILITY
Real-time elastic operational & analytical workloads
Reltio Cloud Data Management Performance by the Numbers:
- Polyglot storage using Apache Cassandra, Spark, Graph, Document and other stores
- Billions of Master Profile entities
- Billions of interactions and transactions for analytics
- Hundreds of Terabytes to Petabytes of data under management
- 22 Locales
- 130+ Countries
- Data Center Regions in North America, Europe and Asia Pacific
Reltio Cloud's Modern Data Management Platform as a Service (PaaS) scales horizontally to deliver elastic performance to support the throughput that you need at anytime. A usage and consumption based model allows on-demand scale up and scale down capacity provisioned based on workloads. Unlike hosted/managed services non-multi-tenant cloud, where capacity is still limited by the hardware originally sized and dedicated to each customer, Reltio Cloud's true multi-cloud, multi-model, multi-tenant architecture provides burst capacity to handle any data access or load scenarios which may have spikes in real-time operational business usage through data-driven applications, or data processing intensive machine learning and predictive analytics.
Reltio was architected from the ground up as a multi-cloud, multi-model platform. It leverages highly scalable persistence technologies like Apache Cassandra (Get the presentation from Reltio's Chief Architect on why Apache Cassandra), Graph technologies, Elastic Search and Apache Spark (Watch a video with Reltio's Lead Data Scientist describing Reltio's innovative use of Apache Spark) along with other AWS services that ensure a high level of redundancy, fault tolerance and availability.
Reltio's multi-model polyglot storage is completely insulated from our customers and partners. We handle and leverage the latest technologies as they become proven, regardless of cloud platform. Our customers and partners realize the benefits as soon as we rollout our new no-unpact upgraded versions (at minimum 3 major releases a year). Reltio’s Modern Data Management platform also incorporates Apache Spark for compute workloads that include analytics and real-time operational high performance REST APIs for master data services.
Reltio continuously performs benchmarks for large datasets in order to improve the efficiency and leverage the latest technologies to support Internet and Big Data scale workloads. A recent example demonstrated 600 Million entity profiles consisting of organizations, locations, customers and various business relationships loaded into Reltio Cloud in a matter of weeks. The load included built-in address verification and matching. Using legacy loading, matching and address verification for such a volume would have taken anywhere from 9-12 months.