DBMS > GBase vs. Geode vs. Oracle vs. Spark SQL

System Properties Comparison GBase vs. Geode vs. Oracle vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Widely used RDBMS

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

www.gbase.cn

geode.apache.org

www.oracle.com/database

spark.apache.org/sql

Technical documentation

geode.apache.org/docs

docs.oracle.com/en/database

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

General Data Technology Co., Ltd.

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Oracle

Apache Software Foundation

Initial release

2004

2002

1980

2014

Current release

GBase 8a, GBase 8s, GBase 8c

1.1, February 2017

23c, September 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

restricted free version is available

Open Source

Apache 2.0

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

C and C++

Scala

Server operating systems

Linux

All OS with a Java VM

the JDK (8 or later) is also required

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

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

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language (OQL)

yes

with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

Java Client API
Memcached protocol
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Java
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

PL/SQL

also stored procedures in Java possible

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Sharding, horizontal partitioning

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

yes

Access rights per client and object definable

fine grained access rights according to SQL-standard

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