DBMS > GeoSpock vs. HBase vs. OpenQM vs. Transwarp Hippo vs. Valentina Server

System Properties Comparison GeoSpock vs. HBase vs. OpenQM vs. Transwarp Hippo 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

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Object-relational database and reports server

Primary database model

Secondary database models

Time Series DBMS

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

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	0.05
Rank	#386	Overall
	#15	Vector DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

geospock.com

hbase.apache.org

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

www.transwarp.cn/en/subproduct/hippo

www.valentina-db.net

Technical documentation

hbase.apache.org/book.html

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

Developer

GeoSpock

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Rocket Software, originally Martin Phillips

Paradigma Software

Initial release

2008

1993

2023

1999

Current release

2.0, September 2019

2.3.4, January 2021

3.4-12

1.0, May 2023

5.7.5

License

Commercial or Open Source

commercial

Open Source

Apache version 2

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++

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

schema-free, schema definition possible

yes

with some exceptions

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

Vector, Numeric and String

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)

yes

APIs and other access methods

JDBC

Java API
RESTful HTTP API
Thrift

RESTful HTTP API

ODBC

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

C++
Java
Python

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

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Single row ACID (across millions of columns)

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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Access rights can be defined down to the item level

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

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Recent citations in the news

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

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

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

GeoSpock launches pioneering new spatial Big Data platform
27 February 2019, Geospatial World

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18 April 2014, SitePoint

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