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ease
features
design
support

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Description

Phoenix serves as a comprehensive open-source observability toolkit tailored for experimentation, evaluation, and troubleshooting purposes. It empowers AI engineers and data scientists to swiftly visualize their datasets, assess performance metrics, identify problems, and export relevant data for enhancements. Developed by Arize AI, the creators of a leading AI observability platform, alongside a dedicated group of core contributors, Phoenix is compatible with OpenTelemetry and OpenInference instrumentation standards. The primary package is known as arize-phoenix, and several auxiliary packages cater to specialized applications. Furthermore, our semantic layer enhances LLM telemetry within OpenTelemetry, facilitating the automatic instrumentation of widely-used packages. This versatile library supports tracing for AI applications, allowing for both manual instrumentation and seamless integrations with tools like LlamaIndex, Langchain, and OpenAI. By employing LLM tracing, Phoenix meticulously logs the routes taken by requests as they navigate through various stages or components of an LLM application, thus providing a clearer understanding of system performance and potential bottlenecks. Ultimately, Phoenix aims to streamline the development process, enabling users to maximize the efficiency and reliability of their AI solutions.

Description

SAP Datasphere serves as a cohesive data experience platform within the SAP Business Data Cloud, aimed at delivering smooth and scalable access to essential business data. By integrating information from both SAP and non-SAP systems, it harmonizes various data environments, facilitating quicker and more precise decision-making. The platform features capabilities such as data federation, cataloging, semantic modeling, and real-time data integration, ensuring organizations maintain consistent and contextualized data across both hybrid and cloud settings. Furthermore, SAP Datasphere streamlines data management by retaining business context and logic, thus providing an all-encompassing view of data that not only drives innovation but also optimizes business processes. This integration ultimately empowers businesses to leverage their data more effectively in an increasingly competitive landscape.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Arize AI
CrewAI
Gemini Enterprise Agent Platform
GitHub
Haystack
JavaScript
JupyterLab
LangChain
LlamaIndex
Mathstral
Mistral 7B
Mistral Large
Mistral NeMo
Mixtral 8x7B
Monda
OpenTelemetry
Python
SAP Business Data Cloud
SAP Business Technology Platform
SAP Store

Integrations

Arize AI
CrewAI
Gemini Enterprise Agent Platform
GitHub
Haystack
JavaScript
JupyterLab
LangChain
LlamaIndex
Mathstral
Mistral 7B
Mistral Large
Mistral NeMo
Mixtral 8x7B
Monda
OpenTelemetry
Python
SAP Business Data Cloud
SAP Business Technology Platform
SAP Store

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Arize AI

Country

United States

Website

docs.arize.com/phoenix

Vendor Details

Company Name

SAP

Founded

1972

Country

Germany

Website

www.sap.com/products/data-cloud/datasphere.html

Product Features

Data Fabric

Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

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