DBMS > GBase vs. GeoSpock vs. Realm vs. Splice Machine

System Properties Comparison GBase vs. GeoSpock vs. Realm vs. Splice Machine

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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

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

Spatial and temporal data processing engine for extreme data scale

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

www.gbase.cn

geospock.com

realm.io

splicemachine.com

Technical documentation

realm.io/docs

splicemachine.com/how-it-works

Developer

General Data Technology Co., Ltd.

GeoSpock

Realm, acquired by MongoDB in May 2019

Splice Machine

Initial release

2004

2014

Current release

GBase 8a, GBase 8s, GBase 8c

2.0, September 2019

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

AGPL 3.0, 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, Java, Python

Java, Javascript

Java

Server operating systems

Linux

hosted

Android
Backend: server-less
iOS
Windows

Linux
OS X
Solaris
Windows

Data scheme

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

yes

temporal, categorical

yes

SQL

Support of SQL

Standard with numerous extensions

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JDBC

JDBC
Native Spark Datasource
ODBC

Supported programming languages

.Net
Java

with Android only
Objective-C
React Native
Swift

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

Server-side scripts

Stored procedures

user defined functions

runs within the applications so server-side scripts are unnecessary

yes

Java

Triggers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

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

Automatic sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

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)

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

In-Memory realm

yes

User concepts

Access control

yes

Access rights for users can be defined per table

yes

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

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
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