# Arize AI vs Mastra

Arize AI records 249,028 monthly visits with +3.2% month-over-month growth and Paid, Contact for Pricing pricing. Mastra records 318,954 monthly visits with -5% growth and Freemium, Contact for Pricing pricing.

| Metric | [Arize AI](https://openaitools.app/tool/arize-com) | [Mastra](https://openaitools.app/tool/mastra) |
| :--- | :--- | :--- |
| Website URL | https://arize.com | https://mastra.ai |
| Categories | Large Language Models (LLMs), AI Agent, AI Monitor, AI Developer Tools | AI Agent, AI Developer Tools, AI Workflow, AI App Builder |
| Pricing Model | Paid, Contact for Pricing | Freemium, Contact for Pricing |
| Monthly Visits | 249,028 | 318,954 |
| MoM Growth Rate | +3.2% | -5% |
| Primary Market | United States | United States |
| Direct Visits | 107,838 | 139,222 |
| Review Score | 4.6 | 4.6 |
| Saved Count | 1 | 0 |
| Supported Platforms | Website | Website |

## Arize AI

Arize is an AI engineering platform built for teams that run generative AI in production. It is split into two products: Arize AX, a managed environment for agent observability, evaluation, and experimentation, and Phoenix, an open-source tracing and evaluation library that teams can self-host when they need full data control. Both rely on OpenInference, the open-source semantic convention for generative AI tracing that the Arize team founded and that is built on OpenTelemetry.

The workflow follows three questions. Observe answers what an agent actually did by capturing every span, trace, and session; Evaluate answers whether quality is improving or regressing using span-level, trace-level, and session-level evals; Learn answers whether a proposed change will help by letting teams test prompts and harnesses before rollout. A datastore for GenAI traces (ADB) keeps data in open formats that connect to warehouses such as BigQuery, Databricks, and Snowflake, and an in-app AI engineering agent named Alyx surfaces issues and drafts review-ready fixes.

The platform integrates with dozens of models, frameworks, and tools, including OpenAI, Anthropic, Google, Amazon Bedrock, LangChain, LangGraph, LlamaIndex, CrewAI, and DSPy. Arize publishes compliance certifications including SOC 2 Type II, ISO 27001, PCI DSS, HIPAA, and GDPR, and supports cloud, hybrid, and self-hosted deployment.

**Pricing & Plans:** Arize uses a paid model with a free entry point: teams can start free or book a demo, while enterprise-scale usage, deployment options, and support are quoted through a contact-sales process. The open-source Phoenix project is free to self-host.

- **End-to-end tracing:** Capture spans, traces, and sessions across agents and LLM calls using OpenInference conventions built on OpenTelemetry, so instrumentation stays portable.
- **Scalable evaluation framework:** Run evaluations at span, trace, and session level to grade retrieval quality, tool use, and final answers across large production datasets.
- **Alyx AI engineering agent:** An in-product agent that inspects traces, diagnoses likely root causes, and proposes fixes that engineers can review before shipping.
- **Phoenix open-source toolkit:** Self-host the leading open-source tracing and eval tool when you need to keep trace data inside your own infrastructure.
- **Warehouse-native trace storage:** ADB stores traces in open formats that connect natively to BigQuery, Databricks, or Snowflake for joint analytics with business data.

**Strengths:** Covers the full loop of observe, evaluate, and improve rather than stopping at dashboards; Backed by OpenInference and OpenTelemetry standards, limiting vendor lock-in on trace formats; Strong enterprise posture with SOC 2, ISO 27001, HIPAA, and GDPR coverage plus self-hosting options; Integrates with a very wide set of models, frameworks, and agent SDKs

**Limitations:** Self-serve pricing is not published, so cost requires a sales conversation; The breadth of features can be overwhelming for small teams shipping their first LLM feature; Full value depends on disciplined instrumentation across the whole application

[Profile (Markdown)](https://openaitools.app/tool/arize-com.md)

## Mastra

Mastra is an open-source TypeScript framework designed for developers who want to build AI agents and workflows in the same language as the rest of their stack. Instead of stitching together a Python agent library plus a separate orchestration layer, teams define typed agents, workflows, and tools directly in TypeScript. Core building blocks include Agents (instructions, models, tools, runtime behavior), Workflows (typed steps, retries, branching), a Harness for multi-mode agents, and Memory that adds durable context through observational memory and semantic recall.

Beyond the framework, Mastra ships an opinionated observability layer: traces, metrics, logs, evaluations, datasets, and scorers, so you can see exactly what an agent did on every run and measure quality before shipping changes. Agents can register on a single Mastra server that runs locally and deploys to Mastra Cloud, and integrations cover major model providers plus MCP servers for tool use.

The project is Apache 2.0 open source and can be self-hosted, while Mastra Cloud adds managed deployment, collaboration, and enterprise controls such as RBAC, SSO, and VPC deployment. Pricing follows a freemium model with a free open-source path and contact-for-pricing cloud plans.

**Pricing & Plans:** Freemium. The framework is Apache 2.0 open source and free to self-host. Mastra Cloud offers paid/managed tiers, with enterprise pricing available on request.

- **Typed agents and workflows:** Define agents with instructions, models, tools, and runtime behavior, then compose typed workflow steps with retries and branching in TypeScript.
- **Durable agent memory:** Give agents long-lived context with observational memory, semantic recall, and thread-aware storage.
- **Built-in observability:** Traces, metrics, logs, and datasets show every model call, tool call, and handoff in a searchable timeline.
- **Evaluations and scorers:** Score agent runs against repeatable checks and experiments before changes reach production.
- **MCP and model integrations:** Connect MCP servers for tool use and route across major model providers including OpenAI, Anthropic, Google Gemini, and xAI.

**Strengths:** TypeScript-first design fits existing JavaScript and Node.js stacks; Apache 2.0 open source with a free self-hosted path; Observability, evals, and datasets are built in rather than bolted on; Memory, workflows, MCP, and multi-provider routing included

**Limitations:** Requires TypeScript and developer familiarity to get value; Cloud and enterprise pricing is quote-based with limited public detail; Fast-moving framework means APIs can change between releases; Best suited to engineering teams, not no-code users

[Profile (Markdown)](https://openaitools.app/tool/mastra.md)

## Frequently Asked Questions

### How do Arize AI and Mastra compare in monthly traffic?

Arize AI has 249,028 monthly visits, while Mastra has 318,954. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Arize AI has a month-over-month growth rate of +3.2%; Mastra has -5%.

### How does pricing compare?

Arize AI: Paid, Contact for Pricing. Arize uses a paid model with a free entry point: teams can start free or book a demo, while enterprise-scale usage, deployment options, and support are quoted through a contact-sales process. The open-source Phoenix project is free to self-host. Mastra: Freemium, Contact for Pricing. Freemium. The framework is Apache 2.0 open source and free to self-host. Mastra Cloud offers paid/managed tiers, with enterprise pricing available on request.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | A robust workflow automation platform uniting visual node-based building with AI agent orchestration and extensive app connectors. | [.md](https://openaitools.app/tool/n8n.md) |
| 2 | [Composio](https://openaitools.app/tool/composio) | 2,782,603 | +22.8% | Freemium, Contact for Pricing | A developer platform providing pre-built integrations, authentication, and execution tools specifically for AI agents across third-party apps. | [.md](https://openaitools.app/tool/composio.md) |
| 3 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | A comprehensive visual platform for building agent workflows and RAG pipelines via a no-code canvas instead of TypeScript. | [.md](https://openaitools.app/tool/dify-ai.md) |
| 4 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/tool/prompts) | 315,624 | -80.2% | Freemium, Contact for Pricing, Free | Excels at experiment tracking and model registry workflows, but is less purpose-built for real-time LLM production observability. | [.md](https://openaitools.app/tool/prompts.md) |
| 5 | [Activepieces](https://openaitools.app/tool/activepieces) | 258,553 | +1.5% | Freemium | An open-source AI automation platform combining conversational workflow drafting, visual flow builders, and prebuilt app connectors. | [.md](https://openaitools.app/tool/activepieces.md) |
| 6 | [Sim AI](https://openaitools.app/tool/sim-ai) | 140,953 | +20.6% | Freemium, Paid (per user/month), and Enterprise with custom pricing; self-hosting free under Apache 2.0 | An open-source AI workspace combining visual workflows and code for building and governing agent systems. | [.md](https://openaitools.app/tool/sim-ai.md) |
| 7 | [Agno](https://openaitools.app/tool/agno) | 140,302 | -3.3% | Contact for Pricing, Free | A popular Python-based agent framework offering modular building blocks, tailored for Python developers rather than TypeScript. | [.md](https://openaitools.app/tool/agno.md) |
| 8 | [Future AGI](https://openaitools.app/tool/future-agi) | 121,741 | -7.8% | Freemium, Usage-based | Includes integrated guardrails and simulation tools, but is less mature for large-scale enterprise production telemetry monitoring. | [.md](https://openaitools.app/tool/future-agi.md) |
| 9 | [Maxim AI](https://openaitools.app/tool/maxim-ai) | 121,351 | +10% | Contact for Pricing, Free Open Source | Features strong testing and prompt evaluation tools, though its monitoring interface is less oriented towards massive telemetry streams. | [.md](https://openaitools.app/tool/maxim-ai.md) |
| 10 | [PromptLayer](https://openaitools.app/tool/promptlayer) | 85,899 | -4.6% | Free Trial, Contact for Pricing | Focuses heavily on prompt management and versioning control, whereas Arize prioritizes end-to-end tracing and ML observability. | [.md](https://openaitools.app/tool/promptlayer.md) |

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Source: https://openaitools.app/compare/arize-com-vs-mastra

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