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What is SAS Data Loader for Hadoop?
Easily import or retrieve your data from Hadoop and data lakes, ensuring it's ready for report generation, visualizations, or in-depth analytics—all within the data lakes framework. This efficient method enables you to organize, transform, and access data housed in Hadoop or data lakes through a straightforward web interface, significantly reducing the necessity for extensive training. Specifically crafted for managing big data within Hadoop and data lakes, this solution stands apart from traditional IT tools. It facilitates the bundling of multiple commands to be executed either simultaneously or in a sequence, boosting overall workflow efficiency. Moreover, you can automate and schedule these commands using the public API provided, enhancing operational capabilities. The platform also fosters collaboration and security by allowing the sharing of commands among users. Additionally, these commands can be executed from SAS Data Integration Studio, effectively connecting technical and non-technical users. Not only does it include built-in commands for various functions like casing, gender and pattern analysis, field extraction, match-merge, and cluster-survive processes, but it also ensures optimal performance by executing profiling tasks in parallel on the Hadoop cluster, which enables the smooth management of large datasets. This all-encompassing solution significantly changes your data interaction experience, rendering it more user-friendly and manageable than ever before, while also offering insights that can drive better decision-making.
What is Apache Parquet?
Parquet was created to offer the advantages of efficient and compressed columnar data formats across all initiatives within the Hadoop ecosystem. It takes into account complex nested data structures and utilizes the record shredding and assembly method described in the Dremel paper, which we consider to be a superior approach compared to just flattening nested namespaces. This format is specifically designed for maximum compression and encoding efficiency, with numerous projects demonstrating the substantial performance gains that can result from the effective use of these strategies. Parquet allows users to specify compression methods at the individual column level and is built to accommodate new encoding technologies as they arise and become accessible. Additionally, Parquet is crafted for widespread applicability, welcoming a broad spectrum of data processing frameworks within the Hadoop ecosystem without showing bias toward any particular one. By fostering interoperability and versatility, Parquet seeks to enable all users to fully harness its capabilities, enhancing their data processing tasks in various contexts. Ultimately, this commitment to inclusivity ensures that Parquet remains a valuable asset for a multitude of data-centric applications.
Integrations Supported
Hadoop
3LC
Amazon Data Firehose
Arroyo
Autymate
IBM Db2 Event Store
MLJAR Studio
Mage Sensitive Data Discovery
Meltano
Microsoft Power BI
Integrations Supported
Hadoop
3LC
Amazon Data Firehose
Arroyo
Autymate
IBM Db2 Event Store
MLJAR Studio
Mage Sensitive Data Discovery
Meltano
Microsoft Power BI
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
SAS
Date Founded
1976
Company Location
United States
Company Website
www.sas.com/en_us/software/data-loader-for-hadoop.html
Company Facts
Organization Name
The Apache Software Foundation
Date Founded
1999
Company Location
United States
Company Website
parquet.apache.org
Categories and Features
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface