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Multi-Model Database Features

Multi-model databases provide an elegant solution to the challenge of managing heterogeneous data.

Benefits of a Multi-Model Database

In contrast to polyglot persistence, where an application integrates multiple database models, a multi-model database naturally supports multiple data models in their native form using a single, integrated backend. Whereas polyglot persistence results in data silos and multiple interfaces that require complex integration workflows, a multi-model database facilitates integrated data and provides a unified interface for data consistency, security, and access.

Just imagine the simplicity your data architecture gains by modeling entities (like patient’s medical record) using the right mix of data models in a multi-model database vs. using polyglot persistence, which will require orchestrating various services by applications to maintain data consistency and security for end-user consumption.


MarkLogic Server

MarkLogic Server is a multi-model database that combines the benefits of document, semantic graph, geospatial, and relational models into a single, scalable, high-performance operational database. It provides native storage for JSON, XML, text, RDF triples, geospatial, and binaries (e.g., PDFs, images, videos) with a unified search and query interface. Hence, you get the flexibility to choose the right mix of data models for your use-case without sacrificing data consistency. For example, you can build a reliable 360 view of your business entities (like customers etc.) to enable multiple use cases (like loyalty programs, personalization etc.).

Tables, SQL Relational RDF Triples, SPARQL Semantic Data JASON/XML, JavaScript/XQuery Documents Tables, SQL Relational RDF Triples, SPARQL Semantic Data JASON/XML, JavaScript/ XQuery Documents

How Does Multi-Model Improve Data Integration?

The ability to store and query multiple data models in multi-model databases results in unprecedented flexibility, operational efficiency, and DevOps agility when integrating data from silos. For instance, relational databases require you to define one agreed-upon uber schema upfront and map all your source data using cumbersome ETL processes that are difficult to maintain as business needs evolve. In contrast, multi-model databases are schema-agnostic so that multiple schemas (or data models) can coexist and you can flexibly evolve the schema to promptly meet new business needs.

As a multi-model database, MarkLogic Server makes it easy to load any data as is and provides flexibility to make iterative changes faster while preserving lineage, provenance, and other metadata. You can add data sources as needed, load structured and unstructured data, and make schema changes to enable new use cases without impacting existing applications or re-ingesting the source data. It is for this reason that MarkLogic Server is the foundation of the MarkLogic Data Hub Platform to integrate, curate, and manage multi-structured data. It makes it possible to integrate data of any type (like IoT, Clickstream, Mainframe, ERP etc.) from any source (like Oracle, SQL Server, Teradata, Hadoop etc.).

What Are Key Features of a Multi-Model Database?

A multi-model database supports multiple data models, indexes, and programming languages to enable multiple use cases while providing a unified data security, governance, and consistency model. With MarkLogic Server, you can expect the following:

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