DBMS > Linter vs. Machbase Neo vs. SAP SQL Anywhere vs. TimesTen

System Properties Comparison Linter vs. Machbase Neo vs. SAP SQL Anywhere vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

RDBMS for high security requirements

TimeSeries DBMS for AIoT and BigData

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

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

linter.ru

machbase.com

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

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

Technical documentation

machbase.com/dbms

help.sap.com/docs/SAP_SQL_Anywhere

docs.oracle.com/database/timesten-18.1

Developer

relex.ru

Machbase

SAP

formerly Sybase

Oracle, TimesTen Performance Software, HP

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

Initial release

1990

2013

1992

1998

Current release

V8.0, August 2023

17, July 2015

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free test version available

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

C and C++

Server operating systems

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

Linux
macOS
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

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

Data scheme

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

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

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

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

ADO.NET
HTTP API
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

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

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

Source-replica replication

Database mirroring

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Transaction concepts

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

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

volatile and lookup table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

fine grained access rights according to SQL-standard

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