Observed Signal · Aug 20, 2026 · Technical Release · Source: DEV Community · Impact: 1/5 · Sentiment: Neutral
Benchmarking Five Graph Databases on 256MB RAM
The author benchmarked five graph databases (CognoDB, Neo4j AuraDB Free, Memgraph, FalkorDB, and ArangoDB) under a tight resource cap (0.5 vCPU / 256MB RAM) using a social-graph SNAP dataset (~18.7k nodes, ~198k edges). Results showed a range of operational and performance issues: Memgraph repeatedly segfaulted at startup across versions and configurations; FalkorDB lost all data after an environment restart due to an incorrect bind mount path and ignored persistence flags; Neo4j AuraDB exhibited a near-constant ~220ms per-query latency floor suggesting a fixed request cost; CognoDB was fastest on most queries but had one query pattern where it performed worst. Full methodology and raw results are available in the linked GitHub repository.
Technical benchmarking of graph databases under constrained free-tier resources; useful to engineers but of limited direct impact to the broader AdTech/MarTech industry.
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Key Takeaways & Evidence Grounding
- CognoDB Cloud's free tier provides a graph database instance with 0.5 vCPU and 256MB of RAM.
- The benchmark compared CognoDB, Neo4j AuraDB Free, Memgraph, FalkorDB, and ArangoDB using the same ~18.7k-node / ~198k-edge SNAP dataset and identical query patterns under a 0.5 vCPU / 256MB RAM cap.
- Memgraph crashed immediately on startup with a reproducible segfault across multiple versions and with various runtime/configuration changes.
- FalkorDB lost all data after an environment restart due to the host bind mount pointing at the wrong in-container data directory and persistence flags being silently ignored.
- Neo4j AuraDB showed an almost constant ~220ms per-query latency floor across trivial and complex queries, indicating a fixed request overhead.
Connected Companies & Entities
2 Entities mapped“I took CognoDB and lined it up against four other graph databases Neo4j AuraDB, FalkorDB, and ArangoDB gave every single one of them the sam...”
“Full methodology, every query definition, every raw result, and the complete reproducible benchmark harness are in the GitHub repo.”
Ontology Mapping & Concepts
Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
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