RDF & semantic platforms
Apache Jena, RDF4J, GraphDB, Stardog and TopBraid categories for standards-based graphs, SPARQL, reasoning and validation.
Vendor-neutral architecture
Choose technology around the meaning and workload.
SDS designs semantic architectures that can work with established RDF platforms, property graphs, data platforms, streaming systems, catalogs, BI tools and AI services. A named technology below indicates a compatibility category or implementation option—not a partnership or endorsement.
Property graphs
Neo4j and comparable platforms where traversal performance and application-centric graph structures lead.
Lakehouse & warehouse
Databricks, Snowflake and cloud data platforms as governed analytical sources and semantic data-product consumers.
Streaming & integration
Kafka, APIs and event-processing patterns that attach identity, provenance and meaning during data movement.
Catalog & governance
Semantic alignment with enterprise catalogs, business glossaries, lineage platforms and policy workflows.
AI, vector & BI
LLM, embedding, vector-search and BI layers grounded in governed concepts, access context and evidence.
Decision guide
Use the right representation for the job.
| Approach | Use when | Watch for |
|---|---|---|
| RDF / OWL | Interoperability, shared semantics and controlled inference matter | Reasoning profile and operating discipline |
| Property graph | Application traversal and developer ergonomics dominate | Portable meaning and constraint strategy |
| Virtualization | Freshness and source control outweigh query latency | Source availability and pushdown behavior |
| Materialization | Repeatable graph analytics and stable snapshots matter | Change data capture and reconciliation |
| Vector search | Semantic similarity over text is useful | Identity, authorization and evidence are separate concerns |
| SHACL | Data expectations must be executable and explainable | Shape lifecycle, severity and exception handling |
Architecture before procurement
Avoid building a platform without a meaning model.
We define the workload, semantics and governance boundary before selecting a deployment pattern.