DBMS > GBase vs. mSQL vs. OrigoDB vs. Solr vs. XTDB

System Properties Comparison GBase vs. mSQL vs. OrigoDB vs. Solr vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

A widely used distributed, scalable search engine based on Apache Lucene

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Search engine

Document store

Secondary database models

Spatial DBMS

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.gbase.cn

hughestech.com.au/products/msql

origodb.com

solr.apache.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

origodb.com/docs

solr.apache.org/resources.html

www.xtdb.com/docs

Developer

General Data Technology Co., Ltd.

Hughes Technologies

Robert Friberg et al

Apache Software Foundation

Juxt Ltd.

Initial release

2004

1994

2009

under the name LiveDB

2006

2019

Current release

GBase 8a, GBase 8s, GBase 8c

4.4, October 2021

9.6.1, May 2024

1.19, September 2021

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

Apache Version 2

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, Java, Python

Java

Clojure

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

yes

supports customizable data types and automatic typing

yes, extensible-data-notation format

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

can be achieved using .NET

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

Standard with numerous extensions

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

Solr Parallel SQL Interface

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC

.NET Client API
HTTP API
LINQ

Java API
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

yes

Java plugins

Triggers

yes

Domain Events

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

none

horizontal partitioning

client side managed; servers are not synchronized

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

yes

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

yes

Role based authorization

yes

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