DBMS > GeoSpock vs. Hive vs. JaguarDB vs. OpenQM vs. Valentina Server

System Properties Comparison GeoSpock vs. Hive vs. JaguarDB vs. OpenQM vs. Valentina Server

Editorial information provided by DB-Engines

Name

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

Description

Spatial and temporal data processing engine for extreme data scale

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Performant, highly scalable DBMS for AI and IoT applications

QpenQM is a high-performance, self-tuning, multi-value DBMS

Object-relational database and reports server

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Multivalue DBMS

Relational DBMS

Secondary database models

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#14	Vector DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

geospock.com

hive.apache.org

www.jaguardb.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.valentina-db.net

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

www.jaguardb.com/support.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

GeoSpock

Apache Software Foundation

initially developed by Facebook

DataJaguar, Inc.

Rocket Software, originally Martin Phillips

Paradigma Software

Initial release

2012

2015

1993

1999

Current release

2.0, September 2019

3.1.3, April 2022

3.3 July 2023

3.4-12

5.7.5

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

GPL V3.0

Open Source

GPLv2, extended commercial license available

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

Java

C++

the server part. Clients available in other languages

Server operating systems

hosted

All OS with a Java VM

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

with some exceptions

yes

Typing

predefined data types such as float or date

yes

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.

yes

Secondary indexes

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like DML and DDL statements

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

JDBC

JDBC
ODBC
Thrift

JDBC
ODBC

ODBC

Supported programming languages

C++
Java
PHP
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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.

yes

User concepts

Access control

Access rights for users can be defined per table

Access rights for users, groups and roles

rights management via user accounts

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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Recent citations in the news

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

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