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What is xSkrape?

Our enthusiasm for various ORM tools, such as Dapper, Hibernate, and Entity Framework, inspired us to discover potential improvements in their features. For a comprehensive look at our initiative, you can visit CodexMicroORM on GitHub, where we address significant topics like enhancing performance, maintaining thread safety, and achieving smooth integration with user interface frameworks such as INotifyPropertyChanged and IDataErrorInfo, while also emphasizing simple configuration and a service-oriented architecture that promotes compatibility with existing classes. CodexMicroORM, or CEF for short, is entirely free and available under the Apache 2.0 license. With a design that prioritizes flexibility, we are thrilled to offer optional paid extensions and tools, including a completely object-oriented database that removes the complexities associated with "object-relational mapping," leading to a more efficient structure and exceptional in-memory performance. Additionally, we are eager to provide detailed insights on our blog, which will not only showcase the advantages of CEF but also explore a range of fascinating data-related topics, inviting you to subscribe for updates even if our framework isn't your immediate focus. We believe that this approach will foster a deeper understanding of the evolving landscape of data management.

What is Voldemort?

Voldemort is not designed to operate as a relational database; it does not seek to maintain arbitrary relationships or comply with ACID principles. It also lacks the functionality of an object database that aims for a seamless mapping of object referencing. Moreover, it does not provide a new layer of abstraction like document orientation. Instead, it functions as a large, distributed, durable, and fault-tolerant hash table. For those employing an Object-Relational (O/R) mapper such as ActiveRecord or Hibernate, this setup can enhance horizontal scalability and availability significantly, though it comes with a notable loss of convenience. When dealing with large-scale applications that require internet-level scalability, systems often consist of multiple services or APIs that are functionally segmented, managing storage across diverse data centers, each with its own horizontally partitioned storage solutions. In such environments, executing arbitrary joins within the database can become unfeasible since not all data resides in a single database instance, which complicates data management further. Consequently, developers must shift their approaches to effectively cope with these limitations, necessitating a careful reevaluation of their data handling practices. This adjustment is crucial to ensure that the system remains efficient and responsive to the diverse needs of the applications it supports.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

$2.49 per month
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

CodeX Enterprises

Company Location

United States

Company Website

www.xskrape.com

Company Facts

Organization Name

Voldemort

Company Website

www.project-voldemort.com/voldemort/

Categories and Features

Data Extraction

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

Categories and Features

Data Replication

Asynchronous Data Replication
Automated Data Retention
Continuous Replication
Cross-Platform Replication
Dashboard
Instant Failover
Orchestration
Remote Database Replication
Reporting / Analytics
Simulation / Testing
Synchronous Data Replication

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