DBMS > GridDB vs. Oracle vs. Oracle NoSQL vs. Splunk

System Properties Comparison GridDB vs. Oracle vs. Oracle NoSQL vs. Splunk

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Editorial information provided by DB-Engines

Name

Description

Scalable in-memory time series database optimized for IoT and Big Data

Widely used RDBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Analytics Platform for Big Data

Primary database model

Time Series DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

Search engine

Secondary database models

Key-value store
Relational 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	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	93.02
Rank	#13	Overall
	#2	Search engines

Website

griddb.net

www.oracle.com/database

www.oracle.com/database/nosql/technologies/nosql

www.splunk.com

Technical documentation

docs.griddb.net

docs.oracle.com/en/database

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.splunk.com/Documentation/Splunk

Developer

Toshiba Corporation

Oracle

Splunk Inc.

Initial release

2013

1980

2011

2003

Current release

5.1, August 2022

23c, September 2023

24.1, May 2024

License

Commercial or Open Source

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

restricted free version is available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

Limited free edition and free developer edition available

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++

C and C++

Java

Server operating systems

Linux

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

Linux
Solaris SPARC/x86

Linux
OS X
Solaris
Windows

Data scheme

yes

Schemaless in JSON and XML columns

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

optional

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

SQL92, SQL-like TQL (Toshiba Query Language)

yes

with proprietary extensions

SQL-like DML and DDL statements

Splunk Search Processing Language for search commands

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

RESTful HTTP API

HTTP REST

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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#
Go
Java
JavaScript (Node.js)
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

can be realized in PL/SQL

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID at container level

ACID

isolation level can be parameterized

configurable

ACID within a storage node (=shard)

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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'

yes

off heap cache

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Access rights for users and roles

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