DBMS > GeoSpock vs. GridGain vs. Machbase Neo vs. Oracle vs. Tibero

System Properties Comparison GeoSpock vs. GridGain vs. Machbase Neo vs. Oracle vs. Tibero

Editorial information provided by DB-Engines

Name

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

Description

Spatial and temporal data processing engine for extreme data scale

GridGain is an in-memory computing platform, built on Apache Ignite

TimeSeries DBMS for AIoT and BigData

Widely used RDBMS

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

geospock.com

www.gridgain.com

machbase.com

www.oracle.com/database

us.tmaxsoft.com/products/tibero

Technical documentation

www.gridgain.com/docs/index.html

machbase.com/dbms

docs.oracle.com/en/database

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

GeoSpock

GridGain Systems, Inc.

Machbase

Oracle

TmaxSoft

Initial release

2007

2013

1980

2003

Current release

2.0, September 2019

GridGain 8.5.1

V8.0, August 2023

23c, September 2023

6, April 2015

License

Commercial or Open Source

commercial

free test version available

commercial

restricted free version is 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

Java, Javascript

Java, C++, .Net

C and C++

C and Assembler

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

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

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
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

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

PL/SQL

also stored procedures in Java possible

Persistent Stored Procedure (PSM)

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

Sharding, horizontal partitioning

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

can be realized in PL/SQL

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

isolation level can be parameterized

ACID

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

volatile and lookup table

yes

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

planned for next version

User concepts

Access control

Access rights for users can be defined per table

Security Hooks for custom implementations

simple password-based access control

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

More information provided by the system vendor

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.