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inlabru alternatives

The best inlabru alternatives in developer tools, ranked by Sparkpulse's velocity_score.

Updated Aug 20, 2026

Looking for the best alternatives to inlabru? Sparkpulse tracks and ranks 12 alternatives in developer tools by shipping velocity — how frequently each ships meaningful updates, verified from official changelogs. For reference, inlabru shipped 0 meaningful updates in the last 30 days and carries a velocity score of 2.5 out of 10 in 2026. The alternatives below are ranked the same way, so you're comparing real release momentum, not marketing claims.

About inlabru

A Bayesian spatial modelling package rebuilding its foundations one breaking release at a time

inlabru wraps INLA for spatial, point-process and latent-Gaussian models in R. It is mid-modernisation: since 2.12.0 cut the sp stack, each release has renamed part of the public surface, standardised how external packages attach custom mappers, or replaced internal machinery. 2.15.0 is the latest step, pairing a new predictor evaluation and linearisation implementation with broom's tidy(), glance() and augment() methods and four non-zero-truncated observation families.

Velocity 2.5 · Last update 32m ago

Read the full inlabru trajectory →

Top 12 alternatives to inlabru

Ranked by recent ship velocity. Tap any card for the full editorial breakdown, or pivot to a head-to-head.

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inlabru vs alternatives — shipping velocity at a glance

Velocity score (0–10) and meaningful releases shipped in the last 30 days, from official changelogs. Higher = shipping faster.

ProductVelocitySparks · 30dFocus areasLatest release
inlabru (baseline)2.50bayesian-modellingspatial-statisticsr-packageDrops sp and ggmap for an sf-native spatial stack
Honeycomb7.52observabilitycanvas-agentsanomaly-detectionAnomaly Detection: Now in Beta
Tailscale6.30networkingscaleapi
Jackett5.00indexerstorrent-searchmaintenance
Skipper5.00reverse-proxykubernetesmemory-footprint
Apache CloudStack5.00iaaslts-branchesmaintenance-releases
Kinsta5.00managed-wordpresshosting-apibot-protection
ToolJet5.00low-codeopentelemetryself-hosted
humind3.81humanitarian-analyticsneeds-assessmentr-package2026 MSNI rollout: HWISE-4 prerequisite, FCLCM, impactR4PHU dropped
campsis3.81pharmacometricsclinical-trial-simulationbreaking-changessnake_case across the API; RxODE compatibility removed
radiatR2.50circular-statisticsanimal-movementr-packageFirst public release
campsismod2.50pharmacometricsmodel-objectsjson-interface
mLLMCelltype2.50llm-consensussingle-cellprovider-integrations

The 12 best inlabru alternatives, in depth

1. Honeycomb · velocity 7.5

Canvas agents gain memory, and onboarding moves into the editor.

Over the last 30 days Honeycomb shipped 2 meaningful updates vs inlabru's 0, most recently “Anomaly Detection: Now in Beta”. Its velocity score of 7.5/10 blends that with longer-term release cadence.

Where inlabru leans on bayesian modelling, spatial statistics and r package, Honeycomb focuses on observability, canvas agents and anomaly detection.

Over the last 30 days Honeycomb has been shipping faster than inlabru — a point in its favour if release momentum matters to you.

2. Tailscale · velocity 6.3

Tailscale is paying down scale in two dimensions: nodes per tailnet, tailnets per org.

Its velocity score of 6.3/10 reflects longer-term release cadence.

Where inlabru leans on bayesian modelling, spatial statistics and r package, Tailscale focuses on networking, scale and api.

Tailscale and inlabru have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.

3. Jackett · velocity 5.0

Daily tags chasing tracker domain moves, login changes and freeleech detection.

Its velocity score of 5.0/10 reflects longer-term release cadence.

Where inlabru leans on bayesian modelling, spatial statistics and r package, Jackett focuses on indexers, torrent search and maintenance.

Jackett and inlabru have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.

4. Skipper · velocity 5.0

Skipper trims a 4x memory regression out of routesrv, days after shipping h2c.

Its velocity score of 5.0/10 reflects longer-term release cadence.

Where inlabru leans on bayesian modelling, spatial statistics and r package, Skipper focuses on reverse proxy, kubernetes and memory footprint.

Skipper and inlabru have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.

5. Apache CloudStack · velocity 5.0

CloudStack ships two LTS branches in lockstep and publishes nothing but pointers.

Its velocity score of 5.0/10 reflects longer-term release cadence.

Where inlabru leans on bayesian modelling, spatial statistics and r package, Apache CloudStack focuses on iaas, lts branches and maintenance releases.

Apache CloudStack and inlabru have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.

6. Kinsta · velocity 5.0

Kinsta is moving MyKinsta's controls into its API, one surface per month.

Its velocity score of 5.0/10 reflects longer-term release cadence.

Where inlabru leans on bayesian modelling, spatial statistics and r package, Kinsta focuses on managed wordpress, hosting api and bot protection.

Kinsta and inlabru have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.

7. ToolJet · velocity 5.0

Observability lands on OpenTelemetry semconv in the LTS train.

Its velocity score of 5.0/10 reflects longer-term release cadence.

Where inlabru leans on bayesian modelling, spatial statistics and r package, ToolJet focuses on low code, opentelemetry and self hosted.

ToolJet and inlabru have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.

8. humind · velocity 3.8

The MSNI humanitarian needs framework as code, rewritten and re-broken every year.

Over the last 30 days humind shipped 1 meaningful update vs inlabru's 0, most recently “2026 MSNI rollout: HWISE-4 prerequisite, FCLCM, impactR4PHU dropped”. Its velocity score of 3.8/10 blends that with longer-term release cadence.

Where inlabru leans on bayesian modelling, spatial statistics and r package, humind focuses on humanitarian analytics, needs assessment and r package.

Over the last 30 days humind has been shipping faster than inlabru — a point in its favour if release momentum matters to you.

9. campsis · velocity 3.8

Campsis breaks its API on purpose: snake_case throughout, RxODE compatibility cut loose.

Over the last 30 days campsis shipped 1 meaningful update vs inlabru's 0, most recently “snake_case across the API; RxODE compatibility removed”. Its velocity score of 3.8/10 blends that with longer-term release cadence.

Where inlabru leans on bayesian modelling, spatial statistics and r package, campsis focuses on pharmacometrics, clinical trial simulation and breaking changes.

Over the last 30 days campsis has been shipping faster than inlabru — a point in its favour if release momentum matters to you.

10. radiatR · velocity 2.5

A circular-statistics toolkit for animal movement, shipped and then tightened in three weeks.

Its velocity score of 2.5/10 reflects longer-term release cadence; its most recent meaningful update was “First public release”.

Where inlabru leans on bayesian modelling, spatial statistics and r package, radiatR focuses on circular statistics, animal movement and r package.

radiatR and inlabru have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.

11. campsismod · velocity 2.5

The model layer under Campsis, renamed in step with it and increasingly JSON-addressable.

Its velocity score of 2.5/10 reflects longer-term release cadence.

Where inlabru leans on bayesian modelling, spatial statistics and r package, campsismod focuses on pharmacometrics, model objects and json interface.

campsismod and inlabru have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.

12. mLLMCelltype · velocity 2.5

Consensus cell-type annotation that keeps adding LLM providers, and keeps fixing how they fail.

Its velocity score of 2.5/10 reflects longer-term release cadence.

Where inlabru leans on bayesian modelling, spatial statistics and r package, mLLMCelltype focuses on llm consensus, single cell and provider integrations.

mLLMCelltype and inlabru have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.

Frequently asked questions

What are the best alternatives to inlabru?

The top inlabru alternatives we currently track in developer tools are Honeycomb, Tailscale, Jackett, Skipper, Apache CloudStack, ranked by recent ship velocity.

How is this list of inlabru alternatives ranked?

Alternatives are ranked by Sparkpulse's velocity_score — release cadence + 30-day spark count + sector-relative ship rate.

Can I compare inlabru directly with one of these alternatives?

Yes — every card has a "Compare with inlabru" link to a side-by-side /compare page.