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What is RaptorXML Server?

In modern businesses, the rise of Big Data trends and XBRL mandates is leading to an ever-increasing influx of data in diverse formats, including XML, XBRL, JSON, and Avro. Fortunately, an advanced and highly efficient engine has been developed to effectively validate, process, transform, and query these extensive data sets. RaptorXML ensures compliance with all relevant XML, XBRL, and JSON standards and is subjected to rigorous regression and conformance testing, using Altova's comprehensive internal test suites alongside recognized industry testing and real-world customer scenarios. As JSON's popularity escalates, so does the imperative for verifying the accuracy and legitimacy of data transactions, a challenge that RaptorXML meets with robust features for JSON syntax validation and adherence to JSON Schema standards. This engine not only simplifies data management but also significantly boosts the reliability of data exchanges, making it an invaluable tool for contemporary enterprises. By leveraging these capabilities, organizations can navigate the complexities of data handling with greater confidence and efficiency.

What is Apache Avro?

Apache Avroâ„¢ is a powerful data serialization system that provides complex data structures along with a compact and efficient binary format, as well as a container file designed for persistent data storage and remote procedure calls (RPC). This system also facilitates easy integration with dynamic programming languages, enhancing its versatility. Importantly, users are not obligated to generate code for reading or writing data files or for employing RPC protocols, as this optional feature is mainly beneficial for statically typed languages. At its core, Avro relies on schemas, which guarantees that the schema utilized during data writing is readily available for future reading, thus eliminating unnecessary overhead for each value and allowing for swift and efficient serialization. The self-describing characteristics of both data and its schema render Avro especially useful for dynamic scripting languages. When data is stored in an Avro file, the corresponding schema is encapsulated within it, enabling any application to subsequently process the files. In cases where a program encounters a different schema upon reading, it can easily adjust to accommodate the change, highlighting Avro's adaptability and strength in managing data. Ultimately, the schema-centric design of Avro not only boosts compatibility across diverse programming environments but also contributes significantly to its overall efficiency in data handling, making it a preferred choice for many developers.

Media

Media

Integrations Supported

Integrations Supported

Apache DataFusion
Apache Hive
Arroyo
Beats
Data Sentinel
Hackolade
SSIS Integration Toolkit
Semarchy xDI
Specmatic
Timeplus
Tonic Ephemeral
Warp 10
e6data

API Availability

API Availability

Has API

Pricing Information

€400 one-time payment
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

Altova

Date Founded

1992

Company Location

United States

Company Website

shop.altova.com/RaptorXMLServer

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

avro.apache.org

Categories and Features

XML Databases

Not specified

Categories and Features

DevOps

Not specified

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