Product comparison

SolarflareDB vs. Zep.

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

Zep 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

DimensionZepSolarflareDB private-beta direction
Primary abstractionTemporal agent context platformTemporal context database
Graph constructionManaged temporal knowledge graphEpisode/fact/entity graph with optional extraction boundary
Freshness contractValidate current ingestion-to-query behaviorWrite bookmark + recent authoritative overlay + index watermarks target
DeploymentReview current hosted optionsCloudflare-managed target, future Core and BYOC
EvaluationUse vendor docs and own benchmarkOpen workload, cost, temporal, entity, and provenance harness target
Pricing positionCredit/subscription model; review current page$0/$5 subsidized entry and action-based overage proposal

When to choose Zep

Choose Zep when you want an established agent-memory and temporal context product and its current API, hosting model, retrieval behavior, and commercial plan fit the workload.

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 you want a lower subsidized entry tier, transparent operation meters, explicit authoritative/derived watermarks, portable object-store recovery, and typed merge semantics.

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and improving temporal correctness, retrieval explainability, and cost transparency—not by claiming every incumbent is obsolete.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.