Why Organizations Choose InterSystems
Today’s enterprises need more than just scalable databases—they need unified platforms that deliver real-time, AI-ready insights without stitching together fragmented services. InterSystems IRIS® combines transactional and analytical processing (HTAP, translytical), data integration, multi-model support, service orchestration, and real-time analytics into a single engine, simplifying architecture and operations.
AWS offers a suite of specialized databases and services (Aurora, Redshift, DynamoDB, Glue, SageMaker, etc.), each optimized for a specific workload. However, integrating these services often introduces complexity, data movement overhead, and latency. In contrast, InterSystems delivers end-to-end capabilities natively in one platform—across OLTP, OLAP, AI/ML, data integration, and real-time streaming.
InterSystems IRIS, as well as being optimized to run on AWS, runs on premises and all major clouds.
Comparison of Key Attributes
Attribute |
InterSystems IRIS |
AWS Database Services |
| Primary Users | Application developers, data engineers, data scientists, analysts, integration architects | Different personas for different services (Aurora for OLTP, Redshift for analytics, Glue for ETL, SageMaker for ML, etc.) |
| Workload Coverage | Real-time hybrid transactional/analytical processing (HTAP), integration, ML ops, multi-model | Distributed across multiple services (Aurora = OLTP, Redshift = OLAP, etc.) |
| Deployment Flexibility | On-premises, hybrid, multi-cloud, or public cloud | AWS cloud only |
| Real-Time Ingestion & Analytics | Native support for streaming ingestion and sub-second analytics across operational and analytical data | Requires integration of independent services including Kinesis (streaming) + Redshift (analytics) + Glue (ETL) |
| Multi-Model Support | Relational, document, vector, object oriented, etc.—all in a single engine | Different engines: DynamoDB (key-value), DocumentDB (document), Aurora (relational), etc. |
| Data Integration & ETL | Built-in integration engine, data fabric, and interoperability across silos | Glue provides ETL; needs orchestration across multiple tools |
| Operational Simplicity | One platform to manage, with fewer moving parts and lower operational overhead | Requires managing and orchestrating multiple AWS services |
| Low-Code / No-Code | InterSystems Data Fabric Studio has visual tools for integration, orchestration, and analytics. | Minimal; most services are developer-oriented |
| AI/ML Support & Deployment | Operationalize models from any framework into real-time, event-driven workflows | SageMaker supports training and deployment; lacks tight integration into real-time operations |
| Security & Governance | Unified, policy-based access control and lineage across all data sources | Policies managed per service; requires coordination across IAM, Lake Formation, etc. |
| Performance at Scale | Proven in mission-critical, real-time environments like healthcare, finance, logistics | High performance per service; latency and complexity grow as services are chained together |
Competitive and Complementary
