Data Hub Platform to Simplify Complex Data & Achieve Data Agility

Our unified data platform gives you a faster, trusted way to unlock value from your enterprise data.

What is MarkLogic Data Hub?

MarkLogic Data Hub is a unified solution that connects all of your multi-structured data and curates it for both transactional and analytical purposes. It works by ingesting data as is from any source, indexing it for immediate query and search, and curating it through a process of harmonization, mastering, and enrichment.

Governance

No Waiting on Complex ETL

• Data ingestion and indexing is immediate
• Streaming or batch
• Structured or unstructured data
• Use familiar tools (MuleSoft, NiFi, Kafka, etc.)

Unified Platform

No Architectural Complexity

• Simplified data management with one consistent, real-time view of data and metadata
• Stable integration hub that can serve many use cases
• Multi-model: JSON, XML, text, geospatial, semantic graph, and relational views
• Built-in full-text search, built-in mastering capability, full transactional consistency
• Less expensive than a ‘build it yourself’ data hub

Smart Curation

No Stalled Projects

• Enrich, harmonize, and master data easier and faster
• Only model what you need, when you need it
• Embedded Machine Learning
• Data Hub UI for ease of use and collaboration

Semantic Graph

Multi-model Data Management

• Manage facts and relationships to add context
• Deliver more intelligent search and insights
• Build advanced knowledge graphs
• Uses RDF and SPARQL standards
• Scales to hundreds of billions of triples

Advanced Security

No Barriers to Sharing Data

• Certified, enterprise-grade security
• Full data lineage tracking and audit capabilities
• Granular controls for roles, permissions, privileges, etc.
• Advanced encryption for data in motion and at rest

Simple Development

No waiting, no wasted effort

• Effortless sharing of consistent, fit-for-purpose, use-case driven data assets
• Agile, DevOps approach to building data-driven microservices (10x faster results than with relational)
• Think in objects, not just rows and columns (though MarkLogic also supports standard SQL)
• Industry-standard APIs and programming languages