Apache Mahout
Apache Mahout is an open-source framework for building scalable machine learning applications. The project has evolved to include Qumat, a unified Python API for building quantum circuits that runs across multiple quantum backends including Qiskit, Cirq, and Amazon Braket, along with QDP for GPU-accelerated classical-to-quantum data encoding.
More than an index entry, but the surface is still mostly links rather than artifacts — the cohort most likely to move a full band from modest, well-targeted work.
API Evangelist profiles Apache Mahout the way a machine reads it — 23 machine-readable artifacts across 2 APIs, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Apache Mahout scores 25.0/100 (emerging), with a separate agent-readiness read of 7/100 (human only). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Apache Mahout
Each block below is one kind of artifact we hold for Apache Mahout. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 2
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
Qumat
Qumat is a unified Python API for building and executing quantum circuits across multiple quantum computing backends including Qiskit, Cirq, and Amazon Braket. It provides a har...
Apache Mahout Samsara
Mahout Samsara is a distributed linear algebra DSL in Scala for building machine learning algorithms on Apache Spark. It provides matrix decompositions, collaborative filtering,...
Pricing Plans 1
Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.
Published pricing tiers and plan structures.
Rate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
Apache Mahout Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.
Cost, billing, and metering signals for API financial operations.
Apache Mahout Finops
FINOPSFeatures 8
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
Notable capabilities this provider offers.
Hardware-Agnostic Quantum API
Qumat provides a unified API that runs the same quantum circuit code on Qiskit, Cirq, and Amazon Braket backends without modification.
Quantum Gate Operations
Complete library of single-qubit gates (H, X, Y, Z, T, Rx, Ry, Rz, U) and multi-qubit gates (CNOT, Toffoli, SWAP, CSWAP).
Parameterized Quantum Circuits
Support for symbolic parameters in rotation gates for variational quantum algorithms and quantum machine learning.
GPU-Accelerated Data Encoding
QDP provides zero-copy tensor transfer for encoding classical data into quantum states with GPU acceleration.
Distributed Linear Algebra
Samsara DSL enables large-scale matrix operations distributed across Apache Spark clusters.
Collaborative Filtering
Distributed recommendation algorithms including ALS-based collaborative filtering for large-scale datasets.
Clustering
Distributed K-Means, fuzzy K-Means, and spectral clustering algorithms running on Spark.
Dimensionality Reduction
Distributed SVD, PCA, and random projection methods for large-scale feature reduction.
Scroll within the panel for all 8 ·
Security Posture 2
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Use Cases 4
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
What developers build with this provider.
Quantum Machine Learning
Build variational quantum algorithms and quantum neural networks using parameterized circuits via the Qumat API.
Quantum Algorithm Research
Prototype and test quantum algorithms across different hardware backends without rewriting circuit code.
Large-Scale Recommendation
Build distributed recommendation systems processing billions of user-item interactions using Mahout on Spark.
Distributed Clustering
Cluster large datasets using distributed K-Means and other algorithms running on Apache Spark.
Integrations 4
Pre-built integrations with other platforms tell you where this provider already fits in a stack.
Pre-built integrations with other platforms and tools.
Qiskit
IBM Qiskit quantum computing framework as a Qumat execution backend for IBM quantum hardware and simulators.
Cirq
Google Cirq quantum computing framework as a Qumat execution backend for Google quantum hardware.
Amazon Braket
AWS Braket quantum computing service as a Qumat execution backend for cloud quantum hardware.
Apache Spark
Primary distributed computing backend for Mahout Samsara linear algebra and machine learning algorithms.
Resources
Every other property we hold for Apache Mahout — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 1
Portal, sign-up, and the first successful call
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Operate 1
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use
Company 1
The organization behind the API
Other 1
Properties that don't map to a standard resource type
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