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What is WANdisco?

Since its introduction in 2010, Hadoop has become an essential part of the data management landscape. Over the last ten years, many companies have adopted Hadoop to improve their data lake infrastructures. Although Hadoop offered a cost-effective method for storing large volumes of data in a distributed fashion, it also introduced various challenges. Managing these systems required specialized IT expertise, and the constraints of on-premises configurations limited the ability to scale according to changing demand. The complexities of overseeing these on-premises Hadoop setups and the resulting flexibility issues are more effectively addressed with cloud-based solutions. To mitigate potential risks and expenses associated with data modernization efforts, many organizations have chosen to optimize their cloud data migration strategies using WANdisco. Their LiveData Migrator functions as a fully self-service platform, removing the necessity for any WANdisco knowledge or assistance. This strategy not only streamlines the migration process but also enables companies to manage their data transitions more effectively. Ultimately, embracing cloud solutions can lead to better resource allocation and more agile data management practices.

What is Apache Phoenix?

Apache Phoenix effectively merges online transaction processing (OLTP) with operational analytics in the Hadoop ecosystem, making it suitable for applications that require low-latency responses by blending the advantages of both domains. It utilizes standard SQL and JDBC APIs while providing full ACID transaction support, as well as the flexibility of schema-on-read common in NoSQL systems through its use of HBase for storage. Furthermore, Apache Phoenix integrates effortlessly with various components of the Hadoop ecosystem, including Spark, Hive, Pig, Flume, and MapReduce, thereby establishing itself as a robust data platform for both OLTP and operational analytics through the use of widely accepted industry-standard APIs. The framework translates SQL queries into a series of HBase scans, efficiently managing these operations to produce traditional JDBC result sets. By making direct use of the HBase API and implementing coprocessors along with specific filters, Apache Phoenix delivers exceptional performance, often providing results in mere milliseconds for smaller queries and within seconds for extensive datasets that contain millions of rows. This outstanding capability positions it as an optimal solution for applications that necessitate swift data retrieval and thorough analysis, further enhancing its appeal in the field of big data processing. Its ability to handle complex queries with efficiency only adds to its reputation as a top choice for developers seeking to harness the power of Hadoop for both transactional and analytical workloads.

Media

Media

Integrations Supported

APERIO DataWise
Alibaba Cloud
Amazon Web Services (AWS)
Databricks
IBM Cloud
Microsoft Azure
Oracle Cloud Infrastructure

Integrations Supported

3forge
Amazon EMR
Apache Flume
Apache HBase
Apache Hive
Apache Spark
Data Sentinel
Hadoop
NoSQL
Python
SQL
Salesforce Data 360
Trino

API Availability

API Availability

Has API

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Free
Free Version

Supported Platforms

SaaS
On-Prem

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

WANdisco

Date Founded

2005

Company Location

United States

Company Website

www.wandisco.com/use-cases/cloud-migration

Company Facts

Organization Name

Apache Software Foundation

Company Website

phoenix.apache.org

Categories and Features

Cloud Migration

Not specified

Data Integration

Not specified

Categories and Features

Embedded Database

Not specified

Relational Database

Not specified

SQL Databases

Not specified

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