Source-available SEI

Open-source Jellyfish and LinearB alternative: a full comparison

By the CodPal team · Updated 17 August 2026

What Jellyfish and LinearB are actually good at

It is worth being honest about this, because a comparison that pretends the incumbents are bad is a comparison you should not trust.

Jellyfish is built for the executive end of the problem. Its strongest suit is allocation and business alignment — tying engineering effort to initiatives, products and capitalisable work in a form a CFO will accept, and doing so across a large organisation. If your actual question is "what did we spend the last two quarters of engineering capacity on, expressed in money", Jellyfish was designed for that conversation.

LinearB is stronger at the team-and-workflow end. Beyond dashboards it ships automation — its gitStream product applies policy to pull requests, routes reviews, and nudges teams in the tools they already use. That "measure, then automatically do something about it" loop is genuinely useful and is not something a pure analytics tool replicates.

Both are polished, both have real support organisations, and both remove all infrastructure work from your plate. Those are the things you are paying for.

Where the money goes

This is usually what starts the search. As of August 2026:

Check these yourself before you quote them. The LinearB figures come from its public pricing page in August 2026 and the Jellyfish position from its pricing page on the same date. Vendor pricing moves, and several third-party "pricing comparison" sites carry figures that do not match either vendor's own page — including a widely repeated claim that LinearB has a permanent free tier for small teams, which its pricing page does not offer.

The structural point matters more than any single number: per-seat SEI pricing scales with the thing you want to grow. Every hire raises the bill for the tool you use to understand your hires. Self-hosted analytics scales with data volume instead, which for engineering metadata is close to free.

Feature-by-feature

The comparison that actually decides this is not "who has more features" — it is whether the specific things you would use are present. Here is the honest map.

The three differences that actually matter

1. Your data does not leave your infrastructure

With either SaaS, your commit metadata, ticket history, PR contents and the shape of your org get shipped to a vendor. For a lot of teams that is a non-issue. For teams in regulated industries, teams with works councils, teams under a customer contract that restricts sub-processors, and teams whose security review takes a quarter, it is the whole conversation.

Deckgauge runs in your own Docker stack against your own Postgres and ClickHouse. The provider tokens you supply are read-only and stay on your box. There is no telemetry back to us. That converts a procurement project into an infrastructure ticket.

2. You can read how every number is computed

Every SEI vendor has had the same meeting: a director disputes a number, nobody can explain precisely how it was derived, and the tool loses credibility permanently. Proprietary metric definitions make that meeting unwinnable.

Deckgauge's definitions are in the repository, and each widget has a documentation page stating what it reads, from which provider, and how it can mislead you — see how a widget gets its number. When deployment or incident data is missing, the affected DORA metrics are labelled as proxies rather than quietly presented as measurements.

3. The bill does not grow when you hire

Per-contributor pricing has a perverse effect: teams exclude contractors, drop the intern cohort, or stop analysing a whole department to keep the invoice down — which puts holes in the exact dataset the tool exists to provide. Uncapped analysis means you measure the whole org because there is no reason not to.

Where the paid tools still win

Four situations where we would tell you to buy the SaaS:

• You have no platform capacity. Somebody has to own upgrades, backups and the host. If that person does not exist, self-hosting becomes shelfware within two quarters.
• You need PR workflow automation, not just measurement. LinearB's gitStream has no equivalent here. Deckgauge measures review behaviour; it does not route or gate PRs.
• You need finance-grade capitalisation with an auditor in the room. Deckgauge produces a defensible CapEx/OpEx report, but Jellyfish has spent years on exactly this workflow and the surrounding controls.
• You need developer-experience surveys in the same tool. Deckgauge measures system behaviour from source data. It does not ask engineers how they feel, and those two signals genuinely complement each other.

If none of those apply, the free, self-hosted option is hard to argue against on cost alone. If a managed service is the blocker rather than the software, there is an enterprise plan with SSO, governance and hosting.

Also consider: Apache DevLake

DevLake is the other serious open-source name, and it is a genuinely different shape of thing — an excellent ingestion pipeline that lands normalised engineering data in a database, after which you build the dashboards yourself in Grafana. If you have data engineers and want full control of the model, that is a real advantage. If you want something to open in front of a VP on Monday, it is weeks of work you have to do first. We wrote that comparison up separately: DevLake gives you a database; we give you the product. There is also a broader survey of self-hosted DORA options.

How to evaluate this in two weeks

Do not run a feature-matrix bake-off. Pick the two or three questions you actually need answered this quarter and see which tool answers them with your data.

1. Days 1–2. Stand up Deckgauge locally and connect one real repository and one real Jira or Azure DevOps project. The quickstart is four commands.
2. Days 3–5. Let the intelligence sync backfill, then open the DORA and flow widgets. Sanity-check them against something you already know to be true — a release you remember being slow, a quarter you remember being heavy on bugs. A metrics tool that contradicts your lived experience is either teaching you something or broken, and you need to know which.
3. Days 6–10. Start LinearB's 45-day trial in parallel and ask both the same question. Where do the numbers differ, and can you find out why? This is where readable metric definitions stop being an abstract virtue.
4. Days 11–14. Show one dashboard to the person who will actually consume it. Whether they ask a better question afterwards is the only benchmark that matters.

Frequently asked

Is there a genuinely open-source alternative to Jellyfish and LinearB?

Yes. Deckgauge is a source-available, self-hosted engineering intelligence platform covering DORA metrics, flow and cycle time, code review analytics, investment allocation and roadmaps across Jira, GitHub, GitLab and Azure DevOps. Apache DevLake is the other main open-source option, but it is a data pipeline you build Grafana dashboards on top of rather than a finished product.

How much do Jellyfish and LinearB cost?

As of August 2026, LinearB publishes per-contributor pricing on its website: Essentials at $29 per contributor per month and Enterprise at $59 per contributor per month, both billed annually, with a 45-day free trial and no permanent free tier. Jellyfish does not publish pricing at all — its pricing page states that cost depends on seat count and the modules selected, and routes you to a sales conversation. Check both vendors directly for current figures.

Does self-hosting mean I lose the metrics?

No. Deckgauge computes the same metric families a commercial SEI platform is bought for — the four DORA keys, throughput and cycle time, PR size and review pickup time, review quality, rework rate, investment allocation across features, bugs, tech debt and KTLO, and per-team comparison views. What you trade is the managed-service layer, not the analytics.

What does running Deckgauge actually cost in effort?

It runs as a Docker Compose stack — Postgres, ClickHouse, Redis, Keycloak, plus the app services. Initial setup is four commands. The ongoing cost is real but modest: you own upgrades, backups and the box it runs on. If you have no platform capacity at all, a managed SaaS is a legitimate choice.

Can Deckgauge write to Jira or GitHub?

No. Jira is strictly read-only and all provider integrations only read issues, pull requests, commits and review activity. This matters for procurement: a read-only integration is a much easier security review than one requesting write scopes.