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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 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.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Hadoop Yes 
Acquia CDP No 
Apache Doris Yes 
Apache Zeppelin Yes 
DataNimbus Yes 
IBM watsonx.data integration Yes 
Jupyter Notebook Yes 
Kedro Yes 
Kubernetes Yes 
Mage Dynamic Data Masking Yes 
Mage Static Data Masking Yes 
NVIDIA Magnum IO Yes 
Okera Yes 
PHEMI Health DataLab Yes 
Progress DataDirect Yes 
PySpark Yes 
RadiantOne No 
geoblink Yes 
witboost Yes 

Integrations

Hadoop Yes 
Acquia CDP Yes 
Apache Doris No 
Apache Zeppelin No 
DataNimbus No 
IBM watsonx.data integration No 
Jupyter Notebook No 
Kedro No 
Kubernetes No 
Mage Dynamic Data Masking No 
Mage Static Data Masking No 
NVIDIA Magnum IO No 
Okera No 
PHEMI Health DataLab No 
Progress DataDirect No 
PySpark No 
RadiantOne Yes 
geoblink No 
witboost No 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

$0.014 per hour
Free Trial No 
Free Version Yes 

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/cloud/analytics-engine

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 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 

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