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What is Pepperdata?

Pepperdata's autonomous, application-level cost optimization achieves significant savings of 30-47% for data-heavy tasks like Apache Spark running on Amazon EMR and Amazon EKS, all without requiring any modifications to the application. By utilizing proprietary algorithms, the Pepperdata Capacity Optimizer effectively and autonomously fine-tunes CPU and memory resources in real time, again with no need for changes to application code. The system continuously analyzes resource utilization in real time, pinpointing areas for increased workload, which allows the scheduler to efficiently allocate tasks to nodes that have available resources and initiate new nodes only when current ones reach full capacity. This results in a seamless and ongoing optimization of CPU and memory usage, eliminating delays and the necessity for manual recommendations while also removing the constant need for manual tuning. Moreover, Pepperdata provides a rapid return on investment by immediately lowering wasted instance hours, enhancing Spark utilization, and allowing developers to shift their focus from manual tuning tasks to driving innovation. Overall, this solution not only improves operational efficiency but also streamlines the development process, leading to better resource management and productivity.

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.

Media

Media

Integrations Supported

Apache Spark
AWS Marketplace
Amazon EKS
Amazon EMR
Google Cloud Managed Service for Apache Spark

Integrations Supported

Apache Spark
RadiantOne
Switch Automation

API Availability

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS
Windows
Mac

Supported Platforms

SaaS

Customer Service / Support

Standard Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Pepperdata, Inc.

Date Founded

2012

Company Location

United States

Company Website

www.pepperdata.com

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/

Categories and Features

Application Performance Monitoring (APM)

Baseline Manager
Diagnostic Tools
Full Transaction Diagnostics
Performance Control
Resource Management
Root-Cause Diagnosis
Server Performance
Trace Individual Transactions

Auto Scaling

Not specified

Cloud Cost Management

Cost Reduction Optimization
Dashboard
Data Visualization
Resource Usage Reporting
Roles / Permissions
Spend and Cost Reporting

Categories and Features

Data Analysis

Not specified

Data Science

Not specified

Integration

Not specified

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