DBMS > BaseX vs. MySQL vs. SAP SQL Anywhere vs. Splice Machine vs. TimescaleDB

System Properties Comparison BaseX vs. MySQL vs. SAP SQL Anywhere vs. Splice Machine vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

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

Widely used open source RDBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Native XML DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

basex.org

www.mysql.com

www.sap.com/products/technology-platform/sql-anywhere.html

splicemachine.com

www.timescale.com

Technical documentation

docs.basex.org

dev.mysql.com/doc

help.sap.com/docs/SAP_SQL_Anywhere

splicemachine.com/how-it-works

docs.timescale.com

Developer

BaseX GmbH

Oracle

since 2010, originally MySQL AB, then Sun

SAP

formerly Sybase

Splice Machine

Timescale

Initial release

2007

1995

1992

2014

2017

Current release

10.7, August 2023

8.4.0, April 2024

17, July 2015

3.1, March 2021

2.15.0, May 2024

License

Commercial or Open Source

Open Source

BSD license

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

Apache 2.0

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

Java

C and C++

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

XQuery supports types

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

with proprietary extensions

yes

full PostgreSQL SQL syntax

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
HTTP API
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

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

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

yes, in C/C++, Java, .Net or Perl

yes

Java

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

Multi-source replication
Source-replica replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

multiple readers, single writer

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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.