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ease
features
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support

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Description

Apache Avro™ serves as a system for data serialization, offering intricate data structures and a fast, compact binary format along with a container file for persistent data storage and remote procedure calls (RPC). It also allows for straightforward integration with dynamic programming languages, eliminating the need for code generation when reading or writing data files or implementing RPC protocols; this only becomes a recommended optimization for statically typed languages. Central to Avro's functionality is its reliance on schemas, which accompany the data at all times, ensuring that the schema used for writing is always available during reading. This design choice minimizes the overhead per value, resulting in both rapid serialization and reduced file size. Furthermore, it enhances compatibility with dynamic and scripting languages since the data is entirely self-describing along with its schema. When data is saved in a file, its corresponding schema remains embedded within, allowing for subsequent processing by any compatible program. In instances where the reading program anticipates a different schema, this discrepancy can be resolved with relative ease, showcasing Avro's flexibility and efficiency in data management. Overall, Avro's architecture significantly streamlines the handling of data across a variety of programming environments.

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.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Apache Hive
Data Sentinel
Amazon EMR
Apache DataFusion
Apache Spark
Arroyo
Beats
Hackolade
Hadoop
NoSQL
Python
SQL
SSIS Integration Toolkit
Salesforce Data 360
Semarchy xDI
Specmatic
Timeplus
Trino
Warp 10
e6data

Integrations

Apache Hive
Data Sentinel
Amazon EMR
Apache DataFusion
Apache Spark
Arroyo
Beats
Hackolade
Hadoop
NoSQL
Python
SQL
SSIS Integration Toolkit
Salesforce Data 360
Semarchy xDI
Specmatic
Timeplus
Trino
Warp 10
e6data

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
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

Founded

1999

Country

United States

Website

avro.apache.org

Vendor Details

Company Name

Apache Software Foundation

Website

phoenix.apache.org

Product Features

DevOps

Approval Workflow
Dashboard
KPIs
Policy Management
Portfolio Management
Prioritization
Release Management
Timeline Management
Troubleshooting Reports

Product Features

Relational Database

ACID Compliance
Data Failure Recovery
Multi-Platform
Referential Integrity
SQL DDL Support
SQL DML Support
System Catalog
Unicode Support

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