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What is IBM Analytics for Apache Spark?

IBM Analytics for Apache Spark presents a flexible and integrated Spark service that empowers data scientists to address ambitious and intricate questions while speeding up the realization of business objectives. This accessible, always-on managed service eliminates the need for long-term commitments or associated risks, making immediate exploration possible. Experience the benefits of Apache Spark without the concerns of vendor lock-in, backed by IBM's commitment to open-source solutions and vast enterprise expertise. With integrated Notebooks acting as a bridge, the coding and analytical process becomes streamlined, allowing you to concentrate more on achieving results and encouraging innovation. Furthermore, this managed Apache Spark service simplifies access to advanced machine learning libraries, mitigating the difficulties, time constraints, and risks that often come with independently overseeing a Spark cluster. Consequently, teams can focus on their analytical targets and significantly boost their productivity, ultimately driving better decision-making and strategic growth.

What is Daft?

Daft is a sophisticated framework tailored for ETL, analytics, and large-scale machine learning/artificial intelligence, featuring a user-friendly Python dataframe API that outperforms Spark in both speed and usability. It provides seamless integration with existing ML/AI systems through efficient zero-copy connections to critical Python libraries such as Pytorch and Ray, allowing for effective GPU allocation during model execution. Operating on a nimble multithreaded backend, Daft initially functions locally but can effortlessly shift to an out-of-core setup on a distributed cluster once the limitations of your local machine are reached. Furthermore, Daft enhances its functionality by supporting User-Defined Functions (UDFs) in columns, which facilitates the execution of complex expressions and operations on Python objects, offering the necessary flexibility for sophisticated ML/AI applications. Its robust scalability and adaptability solidify Daft as an indispensable tool for data processing and analytical tasks across diverse environments, making it a favorable choice for developers and data scientists alike.

Media

Media

Integrations Supported

Apache Spark
Amazon Web Services (AWS)
Apache Arrow
Apache Iceberg
Databricks Data Intelligence Platform
Delta Lake
Google Cloud Platform
JSON
Microsoft Azure
PyTorch
Python
RadiantOne
Rust
Switch Automation
Unity Catalog
pandas

Integrations Supported

Apache Spark
Amazon Web Services (AWS)
Apache Arrow
Apache Iceberg
Databricks Data Intelligence Platform
Delta Lake
Google Cloud Platform
JSON
Microsoft Azure
PyTorch
Python
RadiantOne
Rust
Switch Automation
Unity Catalog
pandas

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/analytics/ca/en/technology/cloud-data-services/spark-as-a-service/

Company Facts

Organization Name

Daft

Company Location

United States

Company Website

www.getdaft.io

Categories and Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Integration

Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services

Categories and Features

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

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