DBMS > BaseX vs. Google Cloud Spanner vs. Linter vs. PostgreSQL vs. TimesTen

System Properties Comparison BaseX vs. Google Cloud Spanner vs. Linter vs. PostgreSQL vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

RDBMS for high security requirements

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

In-Memory RDBMS compatible to Oracle

Primary database model

Native XML DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

basex.org

cloud.google.com/spanner

linter.ru

www.postgresql.org

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

Technical documentation

docs.basex.org

cloud.google.com/spanner/docs

www.postgresql.org/docs

docs.oracle.com/database/timesten-18.1

Developer

BaseX GmbH

Google

relex.ru

PostgreSQL Global Development Group

www.postgresql.org/developer

Oracle, TimesTen Performance Software, HP

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

Initial release

2007

2017

1990

1989

1989: Postgres, 1996: PostgreSQL

1998

Current release

10.7, August 2023

16.3, May 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

BSD license

commercial

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

Server operating systems

Linux
OS X
Windows

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

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

Data scheme

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

standard with numerous extensions

yes

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

PL/SQL

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

partitioning by range, list and (since PostgreSQL 11) by hash

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication with 3 replicas for regional instances.

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

multiple readers, single writer

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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