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What is eXtremeDB?

What contributes to the platform independence of eXtremeDB? It features a hybrid data storage approach, allowing for configurations that are entirely in-memory or fully persistent, as well as combinations of both, unlike many other IMDS databases. Additionally, eXtremeDB incorporates its proprietary Active Replication Fabricâ„¢, enabling not only bidirectional replication but also multi-tier replication, which can optimize data transfer across various network conditions through built-in compression techniques. Furthermore, it offers flexibility in structuring time series data by supporting both row-based and column-based formats, enhancing CPU cache efficiency. eXtremeDB can operate as either a client/server architecture or as an embedded system, providing adaptable and speedy data management solutions. With its design tailored for resource-limited, mission-critical embedded applications, eXtremeDB is utilized in over 30 million deployments globally, ranging from routers and satellites to trains and stock market operations, showcasing its versatility across diverse industries.

What is DuckDB?

Managing and storing tabular data, like that in CSV or Parquet formats, is crucial for effective data management practices. It's often necessary to transfer large sets of results to clients, particularly in expansive client-server architectures tailored for centralized enterprise data warehousing solutions. The task of writing to a single database while accommodating multiple concurrent processes also introduces various challenges that need to be addressed. DuckDB functions as a relational database management system (RDBMS), designed specifically to manage data structured in relational formats. In this setup, a relation is understood as a table, which is defined by a named collection of rows. Each row within a table is organized with a consistent set of named columns, where each column is assigned a particular data type to ensure uniformity. Moreover, tables are systematically categorized within schemas, and an entire database consists of a series of these schemas, allowing for structured interaction with the stored data. This organized framework not only bolsters the integrity of the data but also streamlines the process of querying and reporting across various datasets, ultimately improving data accessibility for users and applications alike.

Media

Media

Integrations Supported

DARWIN Core
FreeRTOS
Nucleus
VxWorks
embOS

Integrations Supported

AnalyticsCreator
ElectroNeek
Flyte
GetDot.ai
LanceDB
MotherDuck
Observable
PuppyGraph
SQLife
SkySQL
Streamkap
Supaboard
Tad
Unity Catalog
Vanna.AI

API Availability

Has API

API Availability

Has API

Pricing Information

Licensing terms vary by usage.
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

McObject

Date Founded

2001

Company Location

United States

Company Website

www.mcobject.com

Company Facts

Organization Name

DuckDB

Company Website

duckdb.org

Categories and Features

Big Data

Data Visualization
High Volume Processing
Predictive Analytics

Caching

Not specified

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface

Distributed Databases

Not specified

Embedded Database

Not specified

In-Memory Databases

Not specified

Key-Value Databases

Not specified

SCADA

Archiving & Retention
Data Aggregation
Data Visualization
Real-time Monitoring

SQL Databases

Not specified

Time Series Databases

Not specified

Categories and Features

Database

Not specified

Embedded Database

Not specified

OLAP Databases

Not specified

Query Engines

Not specified

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