DBMS > eXtremeDB vs. GeoSpock vs. Newts vs. OpenQM vs. Oracle Berkeley DB

System Properties Comparison eXtremeDB vs. GeoSpock vs. Newts vs. OpenQM vs. Oracle Berkeley DB

Editorial information provided by DB-Engines

Name

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

Description

Natively in-memory DBMS with options for persistency, high-availability and clustering

Spatial and temporal data processing engine for extreme data scale

Time Series DBMS based on Cassandra

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

Widely used in-process key-value store

Primary database model

Relational DBMS
Time Series DBMS

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Time Series DBMS

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

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Website

www.mcobject.com

geospock.com

opennms.github.io/newts

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

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

www.mcobject.com/docs/extremedb.htm

github.com/OpenNMS/newts/wiki

docs.oracle.com/cd/E17076_05/html/index.html

Developer

McObject

GeoSpock

OpenNMS Group

Rocket Software, originally Martin Phillips

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2001

2014

1993

1994

Current release

8.2, 2021

2.0, September 2019

3.4-12

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

Open Source

commercial license available

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

C and C++

Java, Javascript

Java

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

Linux
OS X
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

yes

schema-free

yes

with some exceptions

schema-free

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.

support of XML interfaces available

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

temporal, categorical

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

ANSI SQL for query only (using Presto)

yes

SQL interfaced based on SQLite is available

APIs and other access methods

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

JDBC

HTTP REST
Java API

Supported programming languages

.Net
C
C#
C++
Java
Lua
Python
Scala

Java

.Net
Basic
C
Java
Objective C
PHP
Python

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

yes

Triggers

yes

by defining events

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

Automatic sharding

Sharding

based on Cassandra

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

selectable replication factor

based on Cassandra

yes

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

based on Cassandra
Immediate Consistency

based on Cassandra

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

Optimistic (MVCC) and pessimistic (locking) strategies available

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 can be defined down to the item level

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more

Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
» more

Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
» more

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

eXtremeDB 8.4 Unveils Exciting New Features and Enhancements
13 May 2024, EE Journal

Latest embedded DBMS supports asymmetric multiprocessing systems
24 May 2023, Embedded

McObject Announces the Release of eXtremeDB/rt 1.2
23 May 2023, Embedded Computing Design

The Data in Hard Real-time SCADA Systems Lets Companies Do More with Less
11 August 2023, Automation.com

McObject Delivers eXtremeDB 8.4 Improving Performance, Security, and Developer Productivity
13 May 2024, Embedded Computing Design

provided by Google News

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, CoinGeek

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

Big data processing techniques to streamline analytics
5 October 2018, TechTarget

Ola acquires GeoSpoc to build next-gen location technology
5 October 2021, The Economic Times

provided by Google News

ACM recognizes far-reaching technical achievements with special awards
26 May 2021, EurekAlert

Margo I. Seltzer | Berkman Klein Center
18 August 2020, Berkman Klein Center

Database Trends Report: SQL Beats NoSQL, MySQL Most Popular -- ADTmag
5 March 2019, ADT Magazine

How to store financial market data for backtesting
26 January 2019, Towards Data Science

The importance of bitcoin nodes and how to start one
9 May 2014, The Merkle News

provided by Google News

Share this page