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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 Spark?

Apache Spark™ is a powerful analytics platform crafted for large-scale data processing endeavors. It excels in both batch and streaming tasks by employing an advanced Directed Acyclic Graph (DAG) scheduler, a highly effective query optimizer, and a streamlined physical execution engine. With more than 80 high-level operators at its disposal, Spark greatly facilitates the creation of parallel applications. Users can engage with the framework through a variety of shells, including Scala, Python, R, and SQL. Spark also boasts a rich ecosystem of libraries—such as SQL and DataFrames, MLlib for machine learning, GraphX for graph analysis, and Spark Streaming for processing real-time data—which can be effortlessly woven together in a single application. This platform's versatility allows it to operate across different environments, including Hadoop, Apache Mesos, Kubernetes, standalone systems, or cloud platforms. Additionally, it can interface with numerous data sources, granting access to information stored in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and many other systems, thereby offering the flexibility to accommodate a wide range of data processing requirements. Such a comprehensive array of functionalities makes Spark a vital resource for both data engineers and analysts, who rely on it for efficient data management and analysis. The combination of its capabilities ensures that users can tackle complex data challenges with greater ease and speed.

Media

Media

Integrations Supported

Hadoop
Alluxio
Amundsen
Apache Doris
Apache Hive
Apache PredictionIO
Archon Data Store
Coginiti
Deep.BI
Delta Lake
E2E Cloud
Kedro
Kubernetes
Onehouse
Oracle Cloud Infrastructure Data Flow
Retina
ScaleOps
Warp 10
definity

Integrations Supported

Hadoop
Alluxio
Amundsen
Apache Doris
Apache Hive
Apache PredictionIO
Archon Data Store
Coginiti
Deep.BI
Delta Lake
E2E Cloud
Kedro
Kubernetes
Onehouse
Oracle Cloud Infrastructure Data Flow
Retina
ScaleOps
Warp 10
definity

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

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

spark.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

Categories and Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Data Analysis

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

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

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