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ease
features
design
support

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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

The Apache Hadoop software library serves as a framework for the distributed processing of extensive data sets across computer clusters, utilizing straightforward programming models. It is built to scale from individual servers to thousands of machines, each providing local computation and storage capabilities. Instead of depending on hardware for high availability, the library is engineered to identify and manage failures within the application layer, ensuring that a highly available service can run on a cluster of machines that may be susceptible to disruptions. Numerous companies and organizations leverage Hadoop for both research initiatives and production environments. Users are invited to join the Hadoop PoweredBy wiki page to showcase their usage. The latest version, Apache Hadoop 3.3.4, introduces several notable improvements compared to the earlier major release, hadoop-3.2, enhancing its overall performance and functionality. This continuous evolution of Hadoop reflects the growing need for efficient data processing solutions in today's data-driven landscape.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon EMR
Apache Spark
Salesforce Data 360
Trino
Apache Bigtop
Datametica
Gurucul
HEAVY.AI
Jupyter Notebook
MLlib
Mage Dynamic Data Masking
Netdata
Oracle Big Data SQL Cloud Service
PacketRanger
Quobyte
SCIKIQ
SingleStore
ThinkData Works
Toad
Warp 10

Integrations

Amazon EMR
Apache Spark
Salesforce Data 360
Trino
Apache Bigtop
Datametica
Gurucul
HEAVY.AI
Jupyter Notebook
MLlib
Mage Dynamic Data Masking
Netdata
Oracle Big Data SQL Cloud Service
PacketRanger
Quobyte
SCIKIQ
SingleStore
ThinkData Works
Toad
Warp 10

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
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

Apache Software Foundation

Founded

1999

Country

United States

Website

hadoop.apache.org

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

Big Data

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

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