DBMS > FatDB vs. GeoSpock vs. Hyprcubd

System Properties Comparison FatDB vs. GeoSpock vs. Hyprcubd

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Spatial and temporal data processing engine for extreme data scale

Serverless Time Series DBMS

Primary database model

Document store
Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Time Series DBMS

Website

geospock.com

hyprcubd.com (offline)

Developer

FatCloud

GeoSpock

Hyprcubd, Inc.

Initial release

2012

Current release

2.0, September 2019

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Javascript

Server operating systems

Windows

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

temporal, categorical

SQL

Support of SQL

Via inetgration in SQL Server

ANSI SQL for query only (using Presto)

SQL-like query language

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC

gRPC (https)

Supported programming languages

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Can implement custom security layer via applications

Access rights for users can be defined per table

token access

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

How GeoSpock is supercharging geospatial analytics
23 February 2021, ComputerWeekly.com

Imagining an 'Everything Connected' World With Geospock | AWS Startups Blog
20 June 2019, AWS Blog

GeoSpock launches Spatial Big Data Platform 2.0
4 September 2019, VanillaPlus

nChain Leads Investment Round in Extreme-scale Data Firm GeoSpock
2 October 2020, AlexaBlockchain

GeoSpock receives $5.4m as strategic investment
5 October 2020, Geospatial World

provided by Google News

Share this page