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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.

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

Equalum
IBM Analytics Engine
Instaclustr
Jupyter Notebook
JupyterLab
Kylo
MLflow
Mage Sensitive Data Discovery
NVMesh
Pavilion HyperOS
RazorThink
Sifflet
TiMi
Tonic Ephemeral
Vaultspeed
Warp 10
Yandex Data Proc
geoblink
witboost

Integrations Supported

Equalum
IBM Analytics Engine
Instaclustr
Jupyter Notebook
JupyterLab
Kylo
MLflow
Mage Sensitive Data Discovery
NVMesh
Pavilion HyperOS
RazorThink
Sifflet
TiMi
Tonic Ephemeral
Vaultspeed
Warp 10
Yandex Data Proc
geoblink
witboost

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

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/analytics/ca/en/technology/cloud-data-services/spark-as-a-service/

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

spark.apache.org

Categories and Features

Data Analysis

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

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Integration

Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services

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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