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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 Amazon EMR?

Amazon EMR is recognized as a top-tier cloud-based big data platform that efficiently manages vast datasets by utilizing a range of open-source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. This innovative platform allows users to perform Petabyte-scale analytics at a fraction of the cost associated with traditional on-premises solutions, delivering outcomes that can be over three times faster than standard Apache Spark tasks. For short-term projects, it offers the convenience of quickly starting and stopping clusters, ensuring you only pay for the time you actually use. In addition, for longer-term workloads, EMR supports the creation of highly available clusters that can automatically scale to meet changing demands. Moreover, if you already have established open-source tools like Apache Spark and Apache Hive, you can implement EMR on AWS Outposts to ensure seamless integration. Users also have access to various open-source machine learning frameworks, including Apache Spark MLlib, TensorFlow, and Apache MXNet, catering to their data analysis requirements. The platform's capabilities are further enhanced by seamless integration with Amazon SageMaker Studio, which facilitates comprehensive model training, analysis, and reporting. Consequently, Amazon EMR emerges as a flexible and economically viable choice for executing large-scale data operations in the cloud, making it an ideal option for organizations looking to optimize their data management strategies.

Media

Media

Integrations Supported

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

Integrations Supported

Apache Spark
AWS App Mesh
AWS Data Pipeline
Amazon SageMaker Data Wrangler
Amazon SageMaker Studio
Data Virtuality
Feast
Gurucul
Hadoop
Lyftrondata
Okera
Pepperdata
Privacera
Unravel
Zepl

API Availability

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac

Supported Platforms

SaaS
On-Prem

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

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/emr/

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

Big Data

Not specified

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