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features
design
support

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Write a Review

Description

Apache Spark™ serves as a comprehensive analytics platform designed for large-scale data processing. It delivers exceptional performance for both batch and streaming data by employing an advanced Directed Acyclic Graph (DAG) scheduler, a sophisticated query optimizer, and a robust execution engine. With over 80 high-level operators available, Spark simplifies the development of parallel applications. Additionally, it supports interactive use through various shells including Scala, Python, R, and SQL. Spark supports a rich ecosystem of libraries such as SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming, allowing for seamless integration within a single application. It is compatible with various environments, including Hadoop, Apache Mesos, Kubernetes, and standalone setups, as well as cloud deployments. Furthermore, Spark can connect to a multitude of data sources, enabling access to data stored in systems like HDFS, Alluxio, Apache Cassandra, Apache HBase, and Apache Hive, among many others. This versatility makes Spark an invaluable tool for organizations looking to harness the power of large-scale data analytics.

Description

IBM Analytics for Apache Spark offers a versatile and cohesive Spark service that enables data scientists to tackle ambitious and complex inquiries while accelerating the achievement of business outcomes. This user-friendly, continually available managed service comes without long-term commitments or risks, allowing for immediate exploration. Enjoy the advantages of Apache Spark without vendor lock-in, supported by IBM's dedication to open-source technologies and extensive enterprise experience. With integrated Notebooks serving as a connector, the process of coding and analytics becomes more efficient, enabling you to focus more on delivering results and fostering innovation. Additionally, this managed Apache Spark service provides straightforward access to powerful machine learning libraries, alleviating the challenges, time investment, and risks traditionally associated with independently managing a Spark cluster. As a result, teams can prioritize their analytical goals and enhance their productivity significantly.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AI Squared Yes 
Determined AI Yes 
Equalum Yes 
IBM Data Refinery Yes 
JupyterLab Yes 
Kubernetes Yes 
Lightbits Yes 
MLflow Yes 
NVMesh Yes 
Prodea Yes 
Qlik Staige Yes 
Retina Yes 
SingleStore Yes 
Spark NLP Yes 
Thunder Compute Yes 
Vaultspeed Yes 
Warp 10 Yes 
Xtendlabs Yes 
ZenML Yes 

Integrations

AI Squared No 
Determined AI No 
Equalum No 
IBM Data Refinery No 
JupyterLab No 
Kubernetes No 
Lightbits No 
MLflow No 
NVMesh No 
Prodea No 
Qlik Staige No 
Retina No 
SingleStore No 
Spark NLP No 
Thunder Compute No 
Vaultspeed No 
Warp 10 No 
Xtendlabs No 
ZenML No 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial Yes 
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 No 

Customer Support

Business Hours No 
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) No 
In Person No 

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

spark.apache.org

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

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

Product Features

Big Data

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

Data Analysis

Data Discovery No 
Data Visualization No 
High Volume Processing No 
Predictive Analytics No 
Regression Analysis No 
Sentiment Analysis No 
Statistical Modeling No 
Text Analytics No 

Streaming Analytics

Data Enrichment Yes 
Data Wrangling / Data Prep Yes 
Multiple Data Source Support Yes 
Process Automation Yes 
Real-time Analysis / Reporting No 
Visualization Dashboards No 

Product Features

Data Analysis

Data Discovery No 
Data Visualization No 
High Volume Processing No 
Predictive Analytics No 
Regression Analysis No 
Sentiment Analysis No 
Statistical Modeling No 
Text Analytics No 

Data Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports No 

Integration

Dashboard No 
ETL - Extract / Transform / Load No 
Metadata Management No 
Multiple Data Sources No 
Web Services No 

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