Arize Phoenix vs Deep Lake
Compare data AI Tools
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A
Arize Phoenix
Open source LLM tracing and evaluation that captures spans scores prompts and outputs, clusters failures and offers a hosted AX service with free and enterprise tiers.
Pricing Free, SaaS tiers by quote
Category data
Difficulty Beginner
Type Web App
Status Active
D
Deep Lake
Vector database and data lake for AI that stores text images audio video and embeddings in one place with fast dataloaders and RAG friendly tooling.
Pricing Free / $40 per month
Category data
Difficulty Beginner
Type Web App
Status Active
Feature Tags Comparison
Only in Arize Phoenix
llmobservabilitytracingevaluationopensourceotel
Shared
None
Only in Deep Lake
vector-dbdata-lakeragembeddingsmultimodal
Key Features
Arize Phoenix
- • Open source tracing and evaluation built on OpenTelemetry
- • Span capture for prompts tools model outputs and latencies
- • Clustering to reveal failure patterns across sessions
- • Built in evals for relevance hallucination and safety
- • Compare models prompts and guardrails with custom metrics
- • Self host or use hosted AX with expanded limits and support
Deep Lake
- • Multimodal storage for text images audio video and embeddings in one dataset
- • Vector search with metadata filters for precise retrieval at scale
- • Native dataloaders for PyTorch and TensorFlow to stream training batches
- • Dataset versioning and time travel for reproducibility and audits
- • Namespaces roles and tokens to isolate apps and teams
- • Python SDK and REST that unify ingest index and query
Use Cases
Arize Phoenix
- → Trace and debug RAG pipelines across tools and models
- → Cluster bad answers to identify data or prompt gaps
- → Score outputs for relevance faithfulness and safety
- → Run A B tests on prompts with offline or online traffic
- → Add governance with retention access control and SLAs
- → Share findings with engineering and product via notebooks
Deep Lake
- → Build RAG assistants grounded in governed documents
- → Fine tune vision language models with streamed tensors
- → Centralize product FAQs PDFs and images for support bots
- → Prototype semantic search across tickets and chats
- → Keep training and inference data in one lineage aware store
- → Migrate from brittle pipelines to unified multimodal datasets
Perfect For
Arize Phoenix
ml engineers data scientists and platform teams building LLM apps who need open source tracing evals and an optional hosted path as usage grows
Deep Lake
ml engineers data engineers applied researchers platform teams and startups that need one store for raw data plus embeddings with fast training hooks
Capabilities
Arize Phoenix
Spans and Context Professional
Built in and Custom Intermediate
Clustering and Search Intermediate
Hosted AX Basic
Deep Lake
Multimodal Datasets Professional
Vector Search Professional
Zero copy Dataloaders Intermediate
Versioning and Quotas Intermediate
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