DBMS > OrientDB vs. PouchDB vs. RDF4J vs. Snowflake vs. TimesTen

System Properties Comparison OrientDB vs. PouchDB vs. RDF4J vs. Snowflake vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Multi-model DBMS (Document, Graph, Key/Value)

JavaScript DBMS with an API inspired by CouchDB

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

Cloud-based data warehousing service for structured and semi-structured data

In-Memory RDBMS compatible to Oracle

Primary database model

Document store
Graph DBMS
Key-value store

Document store

RDF store

Relational DBMS

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

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

www.orientdb.com/docs/last/index.html

pouchdb.com/guides

rdf4j.org/documentation

docs.snowflake.net/manuals/index.html

docs.oracle.com/database/timesten-18.1

Developer

OrientDB LTD; CallidusCloud; SAP

Apache Software Foundation

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

Snowflake Computing Inc.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2010

2012

2004

2014

1998

Current release

3.2.29, March 2024

7.1.1, June 2019

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

Java

Server operating systems

All OS with a Java JDK (>= JDK 6)

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Unix
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

yes

RDF Schemas

yes

support of semi-structured data formats (JSON, XML, Avro)

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

via views

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

APIs and other access methods

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

HTTP REST

only for PouchDB Server
JavaScript API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

CLI Client
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript

Java
PHP
Python

JavaScript (Node.js)
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Java, Javascript

View functions in JavaScript

yes

user defined functions

PL/SQL

Triggers

Hooks

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

in-memory storage is supported as well

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles; record level security configurable

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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