Analyst Perspectives

The shift from on-premises server infrastructure to cloud-based and software-as-a-service (SaaS) models has had a profound impact on the data and analytics architecture of many organizations in recent years. More than one-half of participants (59%) in Ventana Research’s Analytics and Data Benchmark research are deploying data and analytics workloads in the cloud, and a further 30% plan to do so. Customer demand for cloud-based consumption models has also had a significant impact on the products and services that are available from data and analytics vendors. Data platform providers, both operational and analytic, have had to adapt to changing customer demand. The initial response — making existing products available for deployment on cloud infrastructure — only scratched the surface in terms of responding to emerging expectations. We now see the next generation of products, designed specifically to deliver innovation by taking advantage of cloud-native architecture, being brought to market both by emerging startups, and established vendors, including InterSystems.

InterSystems is a data platform and data management company. It was founded in 1978 and provides data solutions for healthcare, banking, financial services and logistics. It offers database management, integration and healthcare information systems. The company is particularly well-known in the healthcare sector, where its product portfolio includes HealthShare, its interoperability platform that unifies data from various systems for collaboration and analytics. TrakCare is its healthcare information system to connect systems and processes. Underpinning both healthcare offerings is the company’s data management and analytics functionality, which is also separately available, as InterSystems IRIS, for use in any industry. InterSystems IRIS is the company’s cloud data-management software that enables organizations to develop and deploy data and business applications. It offers tools and capabilities in a unified platform spanning data management, interoperability, transaction processing and analytics. The platform offers a scalable, multi-model database, built-in analytics platform to respond to data in real-time and natural language processing (NLP) tools to analyze unstructured data. InterSystems IRIS was launched in 2017 but was based on already-mature and proven functionality. IRIS combined two existing products, the Caché high-performance, multi-model database and the Ensemble application integration engine, which launched in 1997 and 2003, respectively. This combination of data management and integration capabilities is an important IRIS feature as it helps customers manage the increasing volume and complexity of data. Organizations are demanding more integrated data platforms that can enable them to gain full value from the data assets that are locked away in data and application silos. It is also significant in enabling IRIS to support use-cases that require hybrid data processing to deliver intelligent operational applications infused with the results of machine learning (ML) and analytic processes. With InterSystems IRIS, data is stored once and can be accessed as tables, objects, documents, key-value, or multidimensional arrays. Developers can access data as any model type without the need for abstraction layers or replication between models.

The company recently announced a series of new releases and partnerships, positioning itself as the heart of a data fabric to accelerate and simplify access to data across an entire organization. Illustrating the potential opportunities that adapting to cloud-native architecture provide for delivering innovation, InterSystems has also begun offering InterSystems Cloud Services, providing discreet aspects of the overall IRIS functionality (including SQL data processing and ML) or targeting specific use-cases (such as FHIR Server in healthcare). InterSystems also continues to offer the complete IRIS data platform with availability both on-premises and as a cloud service. Recent releases of InterSystems IRIS include new capabilities and enhancements that can speed up and simplify the creation of smart data fabric architectures, including Embedded Python and IntegratedML, as well as a new facility that lets data analysts and data scientists collaborate more easily.

Becoming data-driven is a time-intensive process and presents many challenges for organizations. The most common challenge is delivering the right data to support critical business needs in real time. Siloed systems across multiple departments often lead to data that is inconsistent, disparate and difficult to interpret. These issues are being compounded as organizations continue to add more applications and data sources, driving interest in data platforms that combine data processing and integration capabilities, as well as the ability to address hybrid operational and analytic data processing. I assert that through 2026, operational data platform providers will continue to invest in hybrid operational and analytic processing capabilities to support growing demand for intelligent operational applications infused with personalization and AI-driven recommendations. InterSystems IRIS supports the majority of development and deployment environments, allowing developers and operations teams to work in their environment of choice. The platform can be deployed on various clouds including Amazon Web Services, Microsoft Azure, Google Cloud Platform, Tencent Cloud, private clouds, on-premises, hybrid, bare metal, and virtual machine environments. InterSystems IRIS and InterSystems IRIS for Health are available as managed cloud services. The new InterSystems Cloud Services, including InterSystems Cloud SQL, InterSystems IntegratedML and InterSystems FHIR Server, are designed to facilitate adoption of IRIS, enabling developers to build applications that utilize discreet aspects of the overall data platform for specific functional requirements. InterSystems positions these capabilities as delivering what it calls a smart data fabric. The concept of a smart data fabric builds on existing data fabric architecture by embedding analytics capabilities, including data exploration, business intelligence (BI), NLP and ML directly within the fabric, making it faster and easier for organizations to gain new insights. In addition to the core database and integration functionality designed to support the development and deployment of operational applications, IRIS also provides a range of capabilities targeted specifically at analytic workloads. InterSystems IRIS Adaptive Analytics offers business users the ability to perform self-service analytic querying directly on the data. It enables them to create a semantic layer and create acceleration structures based on workload analysis. InterSystems IntegratedML enables application developers to develop and use ML models in their applications using automated ML. It allows data scientists to refine the ML models and embed them directly within InterSystems IRIS applications through its native ML runtime support. It offers support for NLP and connectivity with various tools including Spark, Predictive Model Markup Language (PMML), and BI tools (Tableau, Power BI). The company also maintains a core focus on security and reliability, driven by demand from customers in healthcare and finance sectors.

InterSystems has a mature and proven offering for data management and should continue to expand its integration and analytics capabilities, adding more partners to strengthen its ecosystem. Although the focus on healthcare has been lucrative for the company, it has the opportunity to expand its addressable market by targeting its products and services to other industries. InterSystems IRIS can enable users to build ML-enabled applications that connect data and application silos. It provides database management, analytics capabilities, and can integrate with existing infrastructure. InterSystems IRIS also embeds native BI, NLP and full-text search technology for use in applications, simplifying the overall architecture and on-premises or cloud deployments. As a cloud-first data platform, InterSystems IRIS can reduce the need to implement and integrate multiple technologies, resulting in less code, fewer system resources, and less maintenance. I recommend that organizations that are migrating to the cloud and are looking for a platform to provide a consistent, accurate and real-time view of their enterprise data should evaluate InterSystems.

Regards,

Matt Aslett