Storage Decision Executive summary · laboratory measurement data
Git repository Open the full study →

Which database should hold the laboratory's data?

THE PROBLEM

600 GB of laboratory data today.
6 TB within a few years.
It needs one working database.

THE CANDIDATES

Relational (PostgreSQL)
vs
Graph (RDF triplestore).

Decision: Relational vs Graph (RDF):

Relational (PostgreSQL) Graph (RDF)
Average report, today ~6 seconds ~1.6 hours
Average report at 6 TB ~30 seconds ~12 hours
Hardware at 6 TB one ordinary server a 14-server cluster
Ontology remains accessible with Relational (PostgreSQL)
faster on the average everyday report
hardware at 6 TB: $33.6k for PGSQL server instead of a $527.7k RDF cluster
servers needed at 6 TB

Side by side

Relational (PostgreSQL)
✓ recommended
Graph (RDF triplestore)
✗ rejected at scale
Average report, todayat 600 GB about 6 seconds about 1.6 hours; 3 of 7 tasks need more than a day details →
Average report at 6 TBthe 3-year horizon about 30 seconds about 12 hours; 5 of 7 tasks need a day or more details →
Servers needed todayat 600 GB one standard server, $10.5k already two servers with 1.4 TB of memory, $58.7k details →
Servers at 6 TB still one server, $33.6k a 14-server cluster, $527.7k details →
Disk for the same dataat 6 TB 21 TB 91 TB - the graph form stores the same data 4.4x bigger details →

Average everyday report

Today · 600 GB

PostgreSQL
Graph (RDF)

In a few years · 6 TB

PostgreSQL
Graph (RDF)

Bars are to scale within each panel - the blue bar is real, it is just that small. An everyday report that takes hours is a report nobody runs.

What about the other formats?

CSV stays exactly where it belongs - the raw archive coming off the instruments (best compression, byte-reproducible). JSON-LD stays the exchange format for sending data between laboratories. Neither is a working database, so neither was a candidate. SQLite is excellent for a single user up to ~600 GB but does not scale to the shared 6 TB horizon.

And the ontology? It survives intact: semantic, ontology-style access is provided as a virtual layer on top of PostgreSQL (e.g. Ontop OBDA) - the graph view without the graph database's cost.

Recommended next steps

  1. Adopt PostgreSQL as the system of record for laboratory measurement data; keep the raw CSV archive as the source of truth for reprocessing.
  2. Provide ontology and semantic queries as a virtual RDF layer over PostgreSQL - no data is copied into a triplestore.
  3. Revisit hardware once volume approaches 6 TB: the measured plan is one 16-core server with 551 GB RAM (~$33.6k at July 2026 prices).
Figures at 600 GB and 6 TB are model projections calibrated on a measured benchmark (7 everyday retrieval tasks x 5 storage formats, every result checksum-validated); the "average report" is the geometric mean of the seven tasks, the same averaging the study's scoring uses. Method, raw data and hardware price sources: facts ledger (every number traced to its artifact) · full interactive study · git.boskadoff.com/Public/LabDataStorageEvaluation.
Study: Mary Goncharenko (Tribology Laboratory, University of Florida; internship at Sandia National Laboratories), with the technical assistance of Vasiliy Goncharenko (SoftCreator, LLC).