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Description
Apache Phoenix provides low-latency OLTP and operational analytics on Hadoop by merging the advantages of traditional SQL with the flexibility of NoSQL. It utilizes HBase as its underlying storage, offering full ACID transaction support alongside late-bound, schema-on-read capabilities. Fully compatible with other Hadoop ecosystem tools such as Spark, Hive, Pig, Flume, and MapReduce, it establishes itself as a reliable data platform for OLTP and operational analytics through well-defined, industry-standard APIs. When a SQL query is executed, Apache Phoenix converts it into a series of HBase scans, managing these scans to deliver standard JDBC result sets seamlessly. The framework's direct interaction with the HBase API, along with the implementation of coprocessors and custom filters, enables performance metrics that can reach milliseconds for simple queries and seconds for larger datasets containing tens of millions of rows. This efficiency positions Apache Phoenix as a formidable choice for businesses looking to enhance their data processing capabilities in a Big Data environment.
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
API Access
Has API
Integrations
Apache Spark
Hadoop
Acquia CDP
Amazon EMR
Apache Flume
Apache HBase
Apache Hive
Data Sentinel
Galileo
IBM Cloud Object Storage
Integrations
Apache Spark
Hadoop
Acquia CDP
Amazon EMR
Apache Flume
Apache HBase
Apache Hive
Data Sentinel
Galileo
IBM Cloud Object Storage
Pricing Details
Free
Free Trial
Free Version
Pricing Details
$0.014 per hour
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Apache Software Foundation
Website
phoenix.apache.org
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/cloud/analytics-engine
Product Features
Relational Database
ACID Compliance
Data Failure Recovery
Multi-Platform
Referential Integrity
SQL DDL Support
SQL DML Support
System Catalog
Unicode Support
Product Features
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery