Compare
Jellyfish vs LinearB
LinearB is built for team leads diagnosing delivery bottlenecks; Jellyfish maps engineering time to investment and compliance reporting for finance.
Side by side
| Jellyfish | LinearB | |||||
|---|---|---|---|---|---|---|
| Vendor | Jellyfish.co, Inc. | LinearB, Inc. | ||||
| Pricing model | Quote only | Subscription | ||||
| Free tier | No | Yes | ||||
| Deployment | Cloud | Cloud | ||||
| Open source | No | No | ||||
| Best for | CTOs and finance teams wanting engineering activity translated into investment and compliance reporting. | Engineering leaders wanting automated DORA-metric tracking plus active workflow nudges, not just dashboards. | ||||
| Pricing | Seat-based pricing that varies by number of seats and which modules (AI Impact, Developer Productivity, DevFinOps) are selected; no published rate card. Checked on the vendor's own page on September 21, 2026: no prices are published. Expect to be quoted. | Per-contributor monthly pricing billed annually, with a minimum contributor count per plan.
Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget. | ||||
| Features |
|
|
Verdict
Jellyfish and LinearB both report DORA and related engineering-delivery metrics from Git and CI/CD data, but they are pitched at different readers, and that should decide the choice faster than any feature comparison.
LinearB frames its entire product around the four DORA metrics and adds WorkerB, an automated bot that nudges pull requests toward faster review and can gate merges against policy — it's a tool a team lead opens to diagnose today's bottleneck. Jellyfish is positioned less as a pure DORA tool and more as a bridge between engineering activity and the business: it maps engineering time to strategic investment categories (new features versus maintenance versus tech debt) and includes a DevFinOps module built specifically for R&D tax-credit and software-capitalization reporting, which puts it in front of finance teams and CTOs rather than individual engineering managers.
Choose Jellyfish if
- Finance needs R&D tax-credit or software-capitalization reporting sourced from engineering activity data.
- Leadership wants to see engineering effort mapped to investment categories, not just delivery speed.
- The buyer is a CTO or VP Engineering justifying headcount and spend, not a team lead running daily standups.
Choose LinearB if
- You want a tool a team lead checks regularly to spot and fix delivery bottlenecks.
- Automated pull-request nudging and merge-gating would actually change behavior on your team.
- You don't need investment-allocation or tax/compliance reporting bolted onto the metrics.
What they share
Both connect to GitHub, GitLab and Jira, both report KPI-style delivery metrics without manual time tracking, and both message their data as team-level signal rather than individual scoring. Neither publishes a public rate card — Jellyfish is seat-based and varies by module selection (AI Impact, Developer Productivity, DevFinOps), LinearB is priced per active contributor per month with no published enterprise ceiling.
The honest caveat
Because Jellyfish's core value proposition is connecting engineering data to financial planning and compliance reporting, evaluating it purely on DORA-dashboard quality against LinearB misses the point of why organizations buy it. If your finance team isn't asking for capitalization or tax-credit reporting, that half of Jellyfish's pitch is paid for and unused.
Last reviewed September 22, 2026