DBMS > Dragonfly vs. GBase vs. IBM Cloudant vs. NCache vs. Oracle

System Properties Comparison Dragonfly vs. GBase vs. IBM Cloudant vs. NCache vs. Oracle

Editorial information provided by DB-Engines

Name

Description

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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

Database as a Service offering based on Apache CouchDB

Open-Source and Enterprise in-memory Key-Value Store

Widely used RDBMS

Primary database model

Secondary database models

Document store
Search engine

Using distributed Lucene

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	0.44
Rank	#255	Overall
	#38	Key-value stores

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	2.85
Rank	#95	Overall
	#18	Document stores

Score	0.91
Rank	#196	Overall
	#29	Key-value stores

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Website

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.gbase.cn

www.ibm.com/products/cloudant

www.alachisoft.com/ncache

www.oracle.com/database

Technical documentation

www.dragonflydb.io/docs

cloud.ibm.com/docs/Cloudant

www.alachisoft.com/resources/docs

docs.oracle.com/en/database

Developer

DragonflyDB team and community contributors

General Data Technology Co., Ltd.

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Alachisoft

Oracle

Initial release

2023

2004

2010

2005

1980

Current release

1.0, March 2023

GBase 8a, GBase 8s, GBase 8c

5.3.3, April 2024

23c, September 2023

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Open Source

Enterprise Edition available

commercial

restricted free version is 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++

C, Java, Python

Erlang

C#, .NET, .NET Core, Java

C and C++

Server operating systems

Linux

hosted

Linux
Windows

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

Data scheme

scheme-free

yes

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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 syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

with proprietary extensions

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
C API
JDBC
ODBC

RESTful HTTP/JSON API

IDistributedCache
JCache
LINQ
Proprietary native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
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

Server-side scripts

Stored procedures

Lua

user defined functions

View functions (Map-Reduce) in JavaScript

support for stored procedures with SQL-Server CLR

PL/SQL

also stored procedures in Java possible

Triggers

publish/subscribe channels provide some trigger functionality

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

yes

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication
Source-replica replication

yes, with selectable consistency level

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

atomic operations within a document possible

optimistic locking and pessimistic locking

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Optimistic locking

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

Password-based authentication

yes

Access rights for users can be defined per database

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

fine grained access rights according to SQL-standard

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