Storage Architecture
Our infrastructure layer separates company data according to how it must be stored, retrieved, audited, and recovered.
Different roles, not different brands
The platform can involve structured databases, object storage, indexes, vector stores, logs, and backups. These are different storage roles, not interchangeable brands of the same database.
Workload-specific storage
Structured operational state is generally better represented in schema-controlled stores that support exact queries, joins, transactions, and constraints. Large documents, media, model artifacts, or archival objects may belong in object storage. Lexical and semantic retrieval require index structures optimized for search rather than transactional state. Audit records and backups have different retention and recovery requirements again.
- Structured state
- Objects / archives
- Lexical indexes
- Vector indexes
- Operational logs
- Backup / recovery copies
The architecture connects these representations without pretending one store should perform every workload equally well.
Consistency and lineage
Derived stores need a relationship to their source. A vector index, search index, or cached representation should be rebuildable or traceable to the underlying canonical data where practical.
Otherwise a retrieval layer can become an independent source of truth whose contents drift silently from the systems it was derived from.
Performance and cost
Storage design affects retrieval latency, reliability, cost, and auditability.
Hot operational data may justify faster access than historical archives. Large media can have different retention economics than structured state. Search indexes may be regenerated rather than backed up identically to irreplaceable source records. The correct architecture therefore depends on access pattern and recovery requirement.
Our objective is not one universal data store. It is a coherent storage hierarchy in which each class of information has an appropriate authoritative, searchable, and recoverable representation.
Recovery tier is part of storage design
Not every derived representation requires the same backup strategy. An authoritative operational database may need direct backup and point-in-time recovery. A semantic index may be reproducible from canonical source records and therefore be cheaper to rebuild than to preserve with identical durability. That distinction affects both cost and recovery planning.
Storage also has lifecycle behavior. Historical archives, active operational state, transient caches, model artifacts, and audit history can require different retention periods and access patterns. Treating all information as equally hot and equally permanent produces unnecessary cost and often weaker governance.
We therefore assign storage according to authority, access pattern, reproducibility, retention, and recovery objective, not simply according to data type.