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| Caché | |
|---|---|
| Name | Caché |
| Developer | InterSystems |
| Released | 1990s |
| Programming language | MUMPS / ObjectScript |
| Operating system | Windows NT, UNIX, Linux |
| Genre | database management system |
| License | proprietary |
Caché
Caché is a high-performance, multi-model database and application server developed by InterSystems that combines an object database, a multidimensional key-value store, and a SQL relational interface. It has been used in clinical, financial, and government applications where throughput and low latency are critical, integrating with HL7, FHIR, DICOM, and enterprise systems such as SAP and Oracle Database. The platform emphasizes rapid application development with compiled routines, persistent objects, and native interoperability with languages like Java, .NET Framework, and Python.
The product name originates from the French word "cache" meaning a hiding place, reflecting a design emphasis on in-memory storage and cached data beneath higher-level interfaces; corporate materials and users commonly pronounce it as "cash" or "ka-SHAY". The branding by InterSystems situates the name alongside other database and middleware terms from the 1990s enterprise software era, sharing lexical space with platforms like MUMPS-derived systems and object database offerings such as Versant and ObjectStore.
Caché is defined as a multi-model database management system that exposes data through three primary paradigms: a multidimensional hierarchical storage engine descended from MUMPS globals, an object persistence layer implemented in ObjectScript, and a SQL engine compatible with ODBC and JDBC clients. Implementations of Caché vary by platform edition—Enterprise, Express, and HealthShare-oriented bundles—tailored for interoperability with standards such as HL7 and FHIR and integration with middleware like Microsoft BizTalk Server and Apache Kafka.
Development traces to extensions of the MUMPS language and the evolution of InterSystems products through the 1990s and 2000s, when demands from healthcare providers (notably Epic Systems and regional health information exchanges) and financial institutions drove enhancements in concurrency, scalability, and standards support. Major milestones include adoption of SQL and ODBC/JDBC interfaces to interoperate with Microsoft SQL Server and Oracle Database, integration points for Java EE and .NET Framework, and modernization efforts to support RESTful API patterns and FHIR resource models. The product lineage intersects with events in healthcare IT policy and interoperability initiatives led by organizations such as Centers for Medicare & Medicaid Services and Health Level Seven International.
At its core, Caché uses a persistent, sparse multidimensional array engine (globals) for data storage, providing direct byte-addressable access patterns similar to MUMPS globals used in systems like VistA and RPMS. The server exposes an object database mapping where ObjectScript classes compile to persistent representations that coexist with SQL tables through a unified dictionary. Transactional control employs write-ahead logging, checkpointing, and locking primitives compatible with ACID semantics, enabling distributed master/replica topologies and clustering features used in deployments alongside HAProxy and VMware ESXi infrastructures.
Caché has been widely adopted in clinical information systems, electronic health record integrations, picture archiving and communication systems interfacing with DICOM modalities, and in financial services for low-latency trading and reconciliation engines. Notable application areas include laboratory information systems used by networks integrated with Centers for Disease Control and Prevention reporting, pharmacovigilance platforms interoperating with FDA submissions, and government registries requiring high availability for citizen records. Integrations often leverage adapters to HL7v2, FHIR, SOAP, and REST endpoints and connectors to enterprise systems like SAP ERP and middleware such as IBM MQ.
Benchmarking Caché focuses on transactional throughput, latency, and concurrency under mixed OLTP and analytic workloads. Evaluations often compare Caché with Oracle Database, Microsoft SQL Server, PostgreSQL, and key-value stores like Redis and Amazon DynamoDB using benchmarks derived from TPC-C, custom healthcare transaction mixes, and simulated IoT ingestion patterns. Performance tuning involves cache sizing, global node layout, routine compilation strategies, and I/O subsystem optimization with SSD arrays or NVMe-backed storage; clustering and horizontal scaling are examined with tools such as sysbench and vendor-supplied utilities.
Caché implements access controls, role-based security, audit trails, and encrypted transports (TLS) to meet regulatory compliance in domains governed by HIPAA, GDPR, and sector-specific standards. Consistency is enforced via transactional isolation levels, journaling, and replication mechanisms; disaster recovery practices align with industry frameworks like ISO/IEC 27001 and standards for health data exchange promulgated by ONC. Security testing typically integrates static code analysis for ObjectScript and dependency scanning when connected to Java or .NET Framework components.
Prominent implementations include clinical backends for electronic health records used by vendors such as Epic Systems integrations, regional health information exchange deployments involving Health Information Exchange networks, and proprietary financial systems in trading firms where low-latency state management is essential. InterSystems also bundles Caché technology into products like HealthShare and interoperability platforms that interact with FHIR servers, analytics tools like SAS and Tableau, and enterprise integration patterns realized with MuleSoft and Microsoft BizTalk Server.
Category:Proprietary database management systems