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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

IBM Analytics Engine offers a unique architecture for Hadoop clusters by separating the compute and storage components. Rather than relying on a fixed cluster with nodes that serve both purposes, this engine enables users to utilize an object storage layer, such as IBM Cloud Object Storage, and to dynamically create computing clusters as needed. This decoupling enhances the flexibility, scalability, and ease of maintenance of big data analytics platforms. Built on a stack that complies with ODPi and equipped with cutting-edge data science tools, it integrates seamlessly with the larger Apache Hadoop and Apache Spark ecosystems. Users can define clusters tailored to their specific application needs, selecting the suitable software package, version, and cluster size. They have the option to utilize the clusters for as long as necessary and terminate them immediately after job completion. Additionally, users can configure these clusters with third-party analytics libraries and packages, and leverage IBM Cloud services, including machine learning, to deploy their workloads effectively. This approach allows for a more responsive and efficient handling of data processing tasks.

Description

Effortlessly load your data into or extract it from Hadoop and data lakes, ensuring it is primed for generating reports, visualizations, or conducting advanced analytics—all within the data lakes environment. This streamlined approach allows you to manage, transform, and access data stored in Hadoop or data lakes through a user-friendly web interface, minimizing the need for extensive training. Designed specifically for big data management on Hadoop and data lakes, this solution is not simply a rehash of existing IT tools. It allows for the grouping of multiple directives to execute either concurrently or sequentially, enhancing workflow efficiency. Additionally, you can schedule and automate these directives via the public API provided. The platform also promotes collaboration and security by enabling the sharing of directives. Furthermore, these directives can be invoked from SAS Data Integration Studio, bridging the gap between technical and non-technical users. It comes equipped with built-in directives for various tasks, including casing, gender and pattern analysis, field extraction, match-merge, and cluster-survive operations. For improved performance, profiling processes are executed in parallel on the Hadoop cluster, allowing for the seamless handling of large datasets. This comprehensive solution transforms the way you interact with data, making it more accessible and manageable than ever.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Hadoop Yes 
Acquia CDP Yes 
Apache Spark Yes 
Galileo Yes 
Impala No 
MINT Yes 
Microsoft 365 No 
Microsoft Power BI No 
SAS Analytics for IoT No 
SAS Anti-Money Laundering No 
SAS Business Intelligence No 
SAS Customer Intelligence No 
SAS Data Management No 
SAS Data Quality No 
SAS Energy Forecasting No 
SAS Enterprise Miner No 
SAS MDM No 
SAS Risk Management No 
Switch Automation Yes 
ZARUS Yes 

Integrations

Hadoop Yes 
Acquia CDP No 
Apache Spark No 
Galileo No 
Impala Yes 
MINT No 
Microsoft 365 Yes 
Microsoft Power BI Yes 
SAS Analytics for IoT Yes 
SAS Anti-Money Laundering Yes 
SAS Business Intelligence Yes 
SAS Customer Intelligence Yes 
SAS Data Management Yes 
SAS Data Quality Yes 
SAS Energy Forecasting Yes 
SAS Enterprise Miner Yes 
SAS MDM Yes 
SAS Risk Management Yes 
Switch Automation No 
ZARUS No 

Pricing Details

$0.014 per hour
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/cloud/analytics-engine

Vendor Details

Company Name

SAS

Founded

1976

Country

United States

Website

www.sas.com/en_us/software/data-loader-for-hadoop.html

Product Features

Data Discovery

Contextual Search No 
Data Classification No 
Data Matching No 
False Positives Reduction No 
Self Service Data Preparation No 
Sensitive Data Identification No 
Visual Analytics No 

Data Visualization

Analytics No 
Content Management No 
Dashboard Creation No 
Filtered Views No 
OLAP No 
Relational Display No 
Simulation Models No 
Visual Discovery No 

Product Features

Data Preparation

Collaboration Tools No 
Data Access No 
Data Blending No 
Data Cleansing No 
Data Governance No 
Data Mashup No 
Data Modeling No 
Data Transformation No 
Machine Learning No 
Visual User Interface No 

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