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What is OpenObserve?

OpenObserve is a powerful open-source observability platform tailored for the management of logs, metrics, and traces, with a strong emphasis on high performance, scalability, and significantly lower costs. It facilitates observability at an immense scale, capable of handling petabytes of data through features like columnar storage data compression and the option to "bring your own bucket" for storage, whether on local disks or cloud services such as S3, GCS, and Azure Blob. Engineered in Rust, OpenObserve employs the DataFusion query engine for direct querying of Parquet files, offering a stateless, horizontally scalable architecture that implements caching strategies for both results and disk, ensuring swift performance even under peak traffic conditions. By following open standards and maintaining compatibility with OpenTelemetry and vendor-neutral APIs, OpenObserve integrates effortlessly into existing monitoring and logging frameworks. Its core features include logs, metrics, traces, frontend monitoring, pipelines, alerts, and detailed dashboards for effective visualizations. This comprehensive platform not only enhances observability but also streamlines data management processes for organizations aiming for operational efficiency. By adopting OpenObserve, businesses can realize significant improvements in their observability practices while managing costs effectively.

What is Arize Phoenix?

Phoenix is an open-source library designed to improve observability for experimentation, evaluation, and troubleshooting. It enables AI engineers and data scientists to quickly visualize information, evaluate performance, pinpoint problems, and export data for further development. Created by Arize AI, the team behind a prominent AI observability platform, along with a committed group of core contributors, Phoenix integrates effortlessly with OpenTelemetry and OpenInference instrumentation. The main package for Phoenix is called arize-phoenix, which includes a variety of helper packages customized for different requirements. Our semantic layer is crafted to incorporate LLM telemetry within OpenTelemetry, enabling the automatic instrumentation of commonly used packages. This versatile library facilitates tracing for AI applications, providing options for both manual instrumentation and seamless integration with platforms like LlamaIndex, Langchain, and OpenAI. LLM tracing offers a detailed overview of the pathways traversed by requests as they move through the various stages or components of an LLM application, ensuring thorough observability. This functionality is vital for refining AI workflows, boosting efficiency, and ultimately elevating overall system performance while empowering teams to make data-driven decisions.

Media

Media

Integrations Supported

OpenTelemetry
Amazon Web Services (AWS)
Apache Parquet
Azure Blob Storage
Kubernetes
Rust

Integrations Supported

OpenTelemetry
Amazon Bedrock
Codestral
Conda
Databricks
Gemini Enterprise Agent Platform
LlamaIndex
Mathstral
Ministral 8B
Mistral Large
Mistral NeMo
Mixtral 8x22B
Mixtral 8x7B
Slack
Vercel

API Availability

Has API

API Availability

Has API

Pricing Information

$0.30 per GB
Free Version

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

OpenObserve

Date Founded

2022

Company Location

United States

Company Website

openobserve.ai/

Company Facts

Organization Name

Arize AI

Company Location

United States

Company Website

docs.arize.com/phoenix

Categories and Features

Observability

Not specified

Categories and Features

AI Observability

Not specified

LLM Evaluation

Not specified

Semantic Layer

Not specified

Telemetry

Not specified

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