DBMS > GeoSpock vs. Heroic vs. OpenQM vs. Valentina Server vs. VoltDB

System Properties Comparison GeoSpock vs. Heroic vs. OpenQM vs. Valentina Server vs. VoltDB

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Object-relational database and reports server

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

geospock.com

github.com/spotify/heroic

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

www.valentina-db.net

www.voltdb.com

Technical documentation

spotify.github.io/heroic

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

docs.voltdb.com

Developer

GeoSpock

Spotify

Rocket Software, originally Martin Phillips

Paradigma Software

VoltDB Inc.

Initial release

2014

1993

1999

2010

Current release

2.0, September 2019

3.4-12

5.7.5

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, C++

Server operating systems

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
OS X
Windows

Linux
OS X

for development

Data scheme

yes

schema-free

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

via Elasticsearch

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

only a subset of SQL 99

APIs and other access methods

JDBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
Basic
C
Java
Objective C
PHP
Python

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

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

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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 can be defined down to the item level

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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More resources

Recent citations in the news

Cambridge-based data analytics startup GeoSpock lands €4.6 million
2 October 2020, EU-Startups

nChain leads investment round in extreme-scale data firm GeoSpock
2 October 2020, CoinGeek

Smart Cities, Autonomous Vehicles, Artificial General Intelligence Robotics: Q&A with Steve Marsh, GeoSpock
16 May 2018, ExchangeWire

GeoSpock’s extreme-scale data mission in $5.4m funding boost
8 October 2020, Cambridge Independent

UK-based database GeoSpock bags $5.4m, to expand into
6 October 2020, Tech in Asia

provided by Google News

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

A Look at Valentina — SitePoint
18 April 2014, SitePoint

MySQL GUI Tools for Windows and Ubuntu/Linux: Top 8 free or open source
7 December 2018, H2S Media

provided by Google News

VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

VoltDB Turns to Real-Time Analytics with NewSQL Database
30 January 2014, Datanami

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

VoltDB Adds Geospatial Support, Cross-Site Replication
28 January 2016, The New Stack

VoltDB Aims for Fast Big Data Development -- ADTmag
29 January 2015, ADT Magazine

provided by Google News

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