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ease
features
design
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

ExtractAny offers a professional, AI-driven solution for extracting structured data from complex sources such as websites, PDFs, and documents. With its no-code visual schema editor, users can easily configure extraction fields and use natural language prompts to specify the exact information needed. The platform excels at parsing nested tables, lists, and dynamic content, ensuring even complicated layouts can be processed accurately. Data extraction tasks run instantly with real-time monitoring and validation to guarantee clean JSON outputs. ExtractAny is suitable for a wide range of data types including contact info, product details, prices, and articles. Its flexible pricing models cater to casual users as well as high-volume enterprise clients, offering priority queues and API access at higher tiers. The tool streamlines data workflows for analysts, developers, and business professionals alike. Supported by global users across 30+ countries, ExtractAny continues to scale with growing demand.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

No images available

Integrations

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

Integrations

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

Pricing Details

No price information available.
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

Founded

1999

Country

United States

Website

avro.apache.org

Vendor Details

Company Name

ExtractAny

Founded

2025

Country

China

Website

extractany.com

Product Features

DevOps

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

Product Features

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

Alternatives

Alternatives

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