Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
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
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
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