Product comparison

SolarflareDB vs. Neo4j.

A decision-oriented comparison of product boundary, temporal semantics, retrieval, consistency, operations, and entry pricing.

Comparison reviewed August 19, 2026 · competitor details must be rechecked before purchase

The architectural difference

Neo4j and SolarflareDB overlap around helping applications recover useful context, but they place the product boundary in different locations. The right choice depends on whether the application needs a specialized retrieval or memory service, a general graph engine, or a unified authoritative temporal context layer.

Comparison statusReviewed August 19, 2026. SolarflareDB is a private-beta product with a locally tested core and staged scale planes; competitor capabilities and prices can change and must be verified directly.

Capability matrix

DimensionNeo4jSolarflareDB private-beta direction
Primary abstractionGeneral-purpose property graph databaseOpinionated temporal context database
Query languageMature Cypher ecosystemTyped APIs and thin declarative context query target
Temporal contextModel in application/schemaRecorded/valid time, supersession, contradiction, provenance defaults
Semantic retrievalProduct and integration dependentNative hybrid context pipeline target
OperationsCapacity-oriented managed graph service or self-managedShard-oriented serverless managed target
Entry pricingCapacity based; review current Aura pricing$0 Spark and $5 Hobby proposal

When to choose Neo4j

Choose Neo4j when mature graph query, broad tooling, graph analytics, Cypher expertise, and a general-purpose graph platform are the dominant requirements.

Retaining a focused system is usually better than introducing a new database merely because it has a broader feature list. Benchmark the actual workload and operational boundary.

When to choose SolarflareDB

Choose SolarflareDB when the main job is agent context with serverless entry economics, hybrid retrieval, source episodes, current/as-of truth, transparent operation meters, and replay defaults.

SolarflareDB should earn adoption by reducing custom context infrastructure and improving temporal correctness, retrieval explainability, and cost transparency—not by claiming every incumbent is obsolete.

How to run a fair evaluation

  1. Use the same source episodes, identity rules, embedding model, and extraction policy.
  2. Measure immediate and settled retrieval after writes.
  3. Include current truth, historical truth, entity aliases, contradictions, and multi-hop questions.
  4. Record context tokens, answer quality, latency, index freshness, and operations cost.
  5. Test deletion, export, duplicate delivery, and concurrent writers.

Use a real workload to decide.

The local prototype shows SolarflareDB’s intended contract. A production evaluation must keep source data, models, prompts, and freshness conditions constant.