DBMS > CouchDB vs. Google Cloud Bigtable vs. LevelDB vs. Oracle vs. RDF4J

System Properties Comparison CouchDB vs. Google Cloud Bigtable vs. LevelDB vs. Oracle vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Widely used RDBMS

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Document store

Key-value store
Wide column store

Key-value store

Relational DBMS

RDF store

Secondary database models

Spatial DBMS

using the Geocouch extension

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	8.30
Rank	#47	Overall
	#7	Document stores

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

couchdb.apache.org

cloud.google.com/bigtable

github.com/google/leveldb

www.oracle.com/database

rdf4j.org

Technical documentation

docs.couchdb.org/en/stable

cloud.google.com/bigtable/docs

github.com/google/leveldb/blob/main/doc/index.md

docs.oracle.com/en/database

rdf4j.org/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Google

Oracle

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2005

2015

2011

1980

2004

Current release

3.3.3, December 2023

1.23, February 2021

23c, September 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

BSD

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C++

C and C++

Java

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

hosted

Illumos
Linux
OS X
Windows

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

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

yes

RDF Schemas

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

via views

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP/JSON API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

C#
C++
Go
Java
JavaScript (Node.js)
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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
PHP
Python

Server-side scripts

Stored procedures

View functions in JavaScript

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

none

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Internal replication in Colossus, and regional replication between two clusters in different zones

none

Multi-source replication
Source-replica replication

none

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 (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

Atomic single-row operations

ACID

isolation level can be parameterized

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

in-memory storage is supported as well

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

Access rights for users can be defined per database

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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