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BigML vs MLJAR Studio

BigML

bigml.com

MLJAR Studio

mljar.com

Side by side

FigureBigMLMLJAR Studio
Price from$833.33/mo$20/mo
Free planYesYes
Free trialYes—
Open source——
WebYes—
Windows—Yes
macOSYesYes
Linux—Yes
APIYes—
Self-hostedYesYes
Plans published74
Spec score · Low-Code Machine Learning Platforms Software9.2 (#1)8.0 (#7)

Plans

BigML

  • FREEFree
  • Basic BigML training$800, paid once
  • BigML Lite$1,000 a month
  • Extra Support$3,000 a month
  • BigML Lite$10,000 a year
  • BigML Lite (annual)$10,000 a year
  • Bronze Enterprise$45,000 a year

BigML pricing →

MLJAR Studio

  • FreeFree
  • Pro$20 a month
  • Business$60 a month
  • Perpetual license$199, paid once

MLJAR Studio pricing →

In their own words

BigML

BigML is a machine-learning platform for classification, regression, forecasting, clustering, anomaly detection, association discovery, and topic modeling. It provides interactive model visualizations, prediction explanations, and field-importance views. Models can be exported in JSON PML or PMML formats for use in programming languages and web, mobile, or IoT applications. OptiML helps select and tune models; WhizzML automates workflows, and Scriptify turns workflows into reusable scripts. Users can work through the REST API and language bindings including Python, Node.js, Ruby, Java, and Swift. Listed integrations include Node-RED, Google Sheets, Zapier, Alexa, Docker, and macOS. BigML runs on web, macOS, API, and self-hosted platforms, with private deployments available on a cloud provider, ISP, or on-premises. The free plan is $0/month and includes up to 60 tasks, a 16 MB per-task dataset limit, and two parallel tasks. Paid plans start at $1,000/month; a three-day trial is available.

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MLJAR Studio

MLJAR Studio is a Python workspace for data analysis, machine-learning experiments, and notebooks, with local-first operation. Ask questions in everyday language and it generates and runs analysis code that remains visible and editable. Its experiment agent can tune models, identify useful features, compare models, track experiments, and produce reports. It works with CSV, Excel, and Parquet files, as well as SQL databases such as PostgreSQL, ClickHouse, and MySQL. Notebook projects can become interactive Mercury web apps hosted on your own infrastructure. Available AI providers include MLJAR AI, OpenAI, Ollama local, and Ollama Cloud; Anthropic and OpenAI-compatible providers are also named. Processing is local by default, but configuring an external provider or MLJAR AI cloud add-on can send data externally. With OpenAI configured, prompts and relevant context may be sent under your settings and provider terms. Plans include Free at free, Pro at $20 a month, Business at $60 a month, and a perpetual license at $199 as a one-time purchase. It runs on Linux, macOS, Windows, and self-hosted environments.

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