Archival Databases, built like modern SaaS

Bespoke archival data platforms that scale and endure.

Relational core. Search-ready. Standards‑aligned. We design PostgreSQL‑first systems for museums, organizations, and private collections—extensible with search and graph when you need it.

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PostgreSQL + JSONBElasticsearch / SolrEAD • DACS • AATCloud‑ready

Core

Relational (Postgres)

Transactions, foreign keys, recursive CTEs, and JSONB flexibility.

Elasticsearch / Solr

OCR and descriptive full‑text search at scale.

Media

External storage

Checksums, paths, and renditions tracked in the database.

Interoperability

Standards‑aligned

DACS, ISAD(G), EAD, and linked data‑ready identifiers.

Outcome

A future‑proof archival platform that grows with your collection.

Why a relational core?

Proven integrity and query power, with modern flexibility via JSONB and integrations.

Integrity by design

Foreign keys and transactions prevent orphan records and partial updates.

Hierarchy aware

Recursive CTEs or ORMs reconstruct collection trees without losing context.

Flexible metadata

Use JSONB for variable technical fields without frequent schema changes.

Search at scale

Pair with Elasticsearch or Solr for OCR and keyword discovery.

Cloud‑ready

Managed Postgres or MySQL, and read replicas for public traffic.

Standards aligned

DACS, ISAD(G), EAD, and AAT integrated into schema and UI.

Reference architecture

Start with PostgreSQL; extend with search and graph when needed. Media lives in object storage with checksums tracked in‑DB.

PostgreSQL core (foreign keys, CTEs, JSONB)
Search index (Elasticsearch/Solr) refreshed on updates
Optional graph/triple store for linked data
Object storage for originals and derivatives; URLs and checksums in DB

Discuss your stack

Admin & Public App

Nuxt • API

PostgreSQL

Relational core + JSONB

Elasticsearch

Full‑text & OCR

Object Storage

S3/GCS + checksums

Graph / RDF (optional)

Linked data

Observability

Backups • Metrics • Alerts

Diagram is illustrative. Components can be tailored to in‑house or managed cloud.

Choose the right core

Recommended

PostgreSQL

Best default for bespoke systems
JSONB for flexible metadata
Great concurrency and extensions (PostGIS, text search)

Good for: GLAM institutions, research groups, and private collections.

MySQL / MariaDB

Widely used (e.g., ArchivesSpace)
Good replication and administrative simplicity
Use InnoDB and integrity‑enforcing settings

Good for: GLAM institutions, research groups, and private collections.

SQLite

Great for prototypes or single‑user workflows
Not ideal for multi‑user web applications
Migrate before public scale

Good for: GLAM institutions, research groups, and private collections.

FAQ

How do you handle large media files? ▾

We store binaries in object storage (S3/GCS/Azure) and keep URIs, renditions, and checksums in the database to keep backups lean and integrity high.

Can you align with DACS, ISAD(G), and EAD? ▾

Yes. We design the schema and UI around these standards and can export EAD/MARC or publish linked data as needed.

What about search and discovery? ▾

We index descriptive metadata and OCR text in Elasticsearch or Solr for fast keyword and faceted search, while the RDBMS remains the source of truth.

Ready to future‑proof your archive?

Let’s map your data model and architecture in a focused discovery session.

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CONTACT

Book a consultation.

Tell us what you’re building. We’ll reply with a clear next step, timeline, and a realistic plan.

Email: headlessflowerdev@gmail.com

Phone: (323) 709-5357