Jaybase vs Provena

Jaybase and Provena are both agent frameworks tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Jaybase

Jaybase stores every agent-generated fact as an immutable, time-stamped record, which means the full sequence of what an agent wrote, when, and why is always recoverable. The vendor describes it as designed for accounting, compliance, and approval workflows where you cannot afford to lose the paper trail. Because it is append-only, there is no overwrite risk — replaying a sequence from any point is a native operation. The library is self-hostable and open-source under AGPL, so it runs inside your own infrastructure without a call home. The project has a small contributor footprint, which means production teams should expect to own gaps in documentation rather than wait for the maintainer to fill them.

Provena

Provena wraps around retrieval steps, tools, and context assembly logic to log where every chunk of data came from, hash it for tamper detection, and surface that audit trail when something breaks or an auditor asks. The vendor describes six framework adapters, an MCP server, PostgreSQL storage, and a policy engine — covering most standard Python-based pipelines without requiring a hosted service. Installation is self-hosted and free. The ceiling appears when your compliance requirement goes beyond audit trails: Provena is a passive tracking library, not an enforcement layer, so it records what happened but does not block a bad retrieval from reaching the model. Teams with hard EU AI Act enforcement obligations pair it with a separate policy gate.

Attribute	Jaybase	Provena
Pricing	Free	Free
Free trial	No	No
Open source	Yes	Yes
Has API	Yes	Yes
Self-hosted option	Yes	Yes
Platforms	Linux, Docker	Python
Released	2026-07	—
Pros	Append-only storage model, so no agent write operation can silently overwrite a prior fact — which means compliance audits have a complete, tamper-evident record rather than the last-write-wins snapshot most databases produce. Native replay support, so when a non-deterministic agent produces a different result on a rerun, you can trace the exact prior sequence and compare it against the new one rather than guessing what changed. Self-hosted with no vendor dependency, so financial or regulated data never leaves your own infrastructure and you are not subject to a hosted service's availability or policy changes. AGPL open-source license, so the full codebase is auditable — which matters in regulated environments where black-box dependencies fail security review. API available, so agents written in any language can append facts without being locked to a specific SDK or framework.	Cryptographic hashing of context chunks at retrieval time, so you can prove after a bad decision whether the data was modified between ingestion and inference — without this, you are reconstructing events from logs that were never designed for forensics. Six framework adapters described in the docs, which means most Python-based RAG or agent stacks get instrumentation without a custom integration layer. PostgreSQL-backed audit storage, so the provenance trail is queryable and retainable for the duration a compliance regime requires — not just written to a flat log that gets rotated. Policy engine that can flag staleness and provenance violations against configurable rules, which means a single misconfigured retriever shows up as an anomaly rather than silently degrading answer quality for weeks. Fully self-hosted and open-source, so the audit data never leaves your infrastructure — a hard requirement for teams in regulated industries where sending context logs to a third-party SaaS is not an option.
Cons	The append-only model has no native support for queries beyond sequential log reads — teams that need to filter, aggregate, or join across fact types have to build that layer themselves, and at any meaningful fact volume that becomes a non-trivial engineering project. With a single maintainer and a small contributor base, documentation gaps are yours to resolve: the README covers the core path, but edge cases in approval workflow design or multi-agent sequencing have no community forum depth to fall back on. Teams that eventually need multi-tenant isolation, role-based fact access, or a managed hosted option will find none of those features in the current architecture — that is the condition under which teams move to a purpose-built audit log service with a commercial support tier.	Provena is a passive observer: it records what entered the context pipeline but does not block a stale or untrusted source from reaching the model. Teams whose compliance requirement is active enforcement — reject this retrieval, do not just log it — must build a blocking layer on top, effectively maintaining two systems where they expected one. With 23 open issues and 2 stars on GitHub at the time of scrape, the project is early-stage and community support is thin. When an adapter breaks against a framework update, the fix timeline depends on a single maintainer; teams with production SLAs are on their own until a patch lands. PostgreSQL is the only described storage backend. Pipelines already standardised on a different data store — a managed cloud warehouse, an observability platform — face a schema translation step or run a second database exclusively for provenance records, which most teams will not accept at scale.

Bottom line

Jaybase and Provena are closely matched on pricing model, openness, and API availability — pick by feature set and platform support in the table above.

Frequently asked questions

What is the difference between Jaybase and Provena?

Jaybase is Free and open source, while Provena is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Jaybase better than Provena?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.