DBMS > GeoSpock vs. H2 vs. OpenQM vs. Vertica

System Properties Comparison GeoSpock vs. H2 vs. OpenQM vs. Vertica

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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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Relational DBMS

Multivalue DBMS

Relational DBMS

Column oriented

Secondary database models

Time Series DBMS

Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Website

geospock.com

www.h2database.com

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

www.vertica.com

Technical documentation

www.h2database.com/html/main.html

vertica.com/documentation

Developer

GeoSpock

Thomas Mueller

Rocket Software, originally Martin Phillips

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2005

1993

2005

Current release

2.0, September 2019

2.2.220, July 2023

3.4-12

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

GPLv2, extended commercial license available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

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

All OS with a Java VM

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Data scheme

yes

with some exceptions

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC

JDBC
ODBC

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Java

.Net
Basic
C
Java
Objective C
PHP
Python

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

yes

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources

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, CoinGeek

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

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

provided by Google News

Vertica on Kubernetes
20 June 2024, blogs.opentext.com

OpenText Analytics Database: The ELT Advantage
9 August 2024, blogs.opentext.com

MapR Hadoop Upgrade Spins YARN, Supports HP Vertica Analytics Platform
31 May 2024, Data Center Knowledge

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK
11 February 2021, AWS Blog

provided by Google News

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