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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

DataLux is an innovative platform designed for effective data management and analytics, specifically created to tackle various data-related issues while facilitating real-time decision-making. Equipped with user-friendly plug-and-play adaptors, it enables the aggregation of extensive data collections and offers the capability to collect and visualize insights instantaneously. Utilize the data lake to anticipate and drive new innovations, while ensuring that data is stored in a manner conducive to modeling. The platform allows for the development of portable applications by leveraging containerization, whether in a public cloud, private cloud, or on-premise environment. It seamlessly integrates diverse time-series market data and inferred information, including stock exchange tick data, market policy actions, relevant cross-industry news, and alternative datasets, to derive causal insights regarding stock markets and macroeconomic factors. By providing valuable insights, DataLux empowers businesses to shape their decisions and foster product innovations effectively. Additionally, it supports interdisciplinary A/B testing throughout the product development lifecycle, from initial ideation to final decision-making, ensuring a comprehensive approach to enhancing design and engineering processes.

Description

JaguarDB facilitates the rapid ingestion of time series data while integrating location-based information. It possesses the capability to index data across both spatial and temporal dimensions effectively. Additionally, the system allows for swift back-filling of time series data, enabling the insertion of significant volumes of historical data points. Typically, time series refers to a collection of data points that are arranged in chronological order. However, in JaguarDB, time series encompasses both a sequence of data points and multiple tick tables that hold aggregated data values across designated time intervals. For instance, a time series table in JaguarDB may consist of a primary table that organizes data points in time sequence, along with tick tables that represent various time frames such as 5 minutes, 15 minutes, hourly, daily, weekly, and monthly, which store aggregated data for those intervals. The structure for RETENTION mirrors that of the TICK format but allows for a flexible number of retention periods, defining the duration for which data points in the base table are maintained. This approach ensures that users can efficiently manage and analyze historical data according to their specific needs.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Vivorbis

Founded

2016

Country

Hungary

Website

www.equinox.is/solutions

Vendor Details

Company Name

JaguarDB

Website

www.datajaguar.com

Product Features

Big Data

Collaboration No 
Data Blends Yes 
Data Cleansing Yes 
Data Mining No 
Data Visualization Yes 
Data Warehousing Yes 
High Volume Processing Yes 
No-Code Sandbox No 
Predictive Analytics Yes 
Templates No 

Product Features

NoSQL Database

Auto-sharding No 
Automatic Database Replication No 
Data Model Flexibility No 
Deployment Flexibility No 
Dynamic Schemas No 
Integrated Caching No 
Multi-Model No 
Performance Management No 
Security Management No 

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