DBMS > Bangdb vs. GeoSpock vs. OpenQM vs. Splice Machine vs. Valentina Server

System Properties Comparison Bangdb vs. GeoSpock vs. OpenQM vs. Splice Machine 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

Converged and high performance database for device data, events, time series, document and graph

Spatial and temporal data processing engine for extreme data scale

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Object-relational database and reports server

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Multivalue DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

bangdb.com

geospock.com

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

splicemachine.com

www.valentina-db.net

Technical documentation

docs.bangdb.com

splicemachine.com/how-it-works

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

Developer

Sachin Sinha, BangDB

GeoSpock

Rocket Software, originally Martin Phillips

Splice Machine

Paradigma Software

Initial release

2012

1993

2014

1999

Current release

BangDB 2.0, October 2021

2.0, September 2019

3.4-12

3.1, March 2021

5.7.5

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

GPLv2, extended commercial license available

Open Source

AGPL 3.0, 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

C, C++

Java, Javascript

Java

Server operating systems

Linux

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

with some exceptions

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

yes

secondary, composite, nested, reverse, geospatial

temporal, categorical

yes

SQL

Support of SQL

SQL like support with command line tool

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

JDBC
Native Spark Datasource
ODBC

ODBC

Supported programming languages

C
C#
C++
Java
Python

.Net
Basic
C
Java
Objective C
PHP
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

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

Server-side scripts

Stored procedures

yes

Java

yes

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Automatic sharding

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

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 concurrency control

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

Access rights for users can be defined per table

Access rights can be defined down to the item level

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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