DBMS > BaseX vs. Graph Engine vs. PouchDB vs. TimesTen

System Properties Comparison BaseX vs. Graph Engine vs. PouchDB vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

JavaScript DBMS with an API inspired by CouchDB

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Native XML DBMS

Graph DBMS
Key-value store

Document store

Relational DBMS

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

Score	1.56
Rank	#141	Overall
	#4	Native XML DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	2.18
Rank	#114	Overall
	#21	Document stores

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

basex.org

www.graphengine.io

pouchdb.com

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

Technical documentation

docs.basex.org

www.graphengine.io/docs/manual

pouchdb.com/guides

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

Developer

BaseX GmbH

Microsoft

Apache Software Foundation

Oracle

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

Initial release

2007

2010

2012

1998

Current release

11.2, August 2024

7.1.1, June 2019

Release 22.1

License

Commercial or Open Source

Open Source

BSD license

Open Source

MIT License

Open Source

commercial

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

Java

.NET and C

JavaScript

Server operating systems

Linux
OS X
Windows

.NET

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

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

XQuery supports types

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.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

C#
C++
F#
Visual Basic

JavaScript

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

yes

View functions in JavaScript

PL/SQL

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

Users with fine-grained authorization concept on 4 levels

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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