DBMS > Axibase vs. MonetDB vs. Sadas Engine vs. TimesTen

System Properties Comparison Axibase vs. MonetDB vs. Sadas Engine vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

A relational database management system that stores data in columns

SADAS Engine is a columnar DBMS specifically designed for high performance in Data warehouse environments

In-Memory RDBMS compatible to Oracle

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Document store

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

Score	0.30
Rank	#258	Overall
	#20	Time Series DBMS

Score	2.00
Rank	#124	Overall
	#62	Relational DBMS

Score	0.00
Rank	#333	Overall
	#138	Relational DBMS

Score	2.40
Rank	#112	Overall
	#55	Relational DBMS

Website

axibase.com/products/axibase-time-series-database

www.monetdb.org

www.sadasengine.com

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

Technical documentation

github.com/axibase/atsd

www.monetdb.org/Documentation

www.sadasengine.com/index.php/downloads/documentation-columnar-db

docs.oracle.com/database/timesten-18.1

Developer

Axibase Corporation

MonetDB BV

SADAS s.r.l.

Oracle, TimesTen Performance Software, HP

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

Initial release

2013

2004

2006

1998

Current release

15585

Oct2020-SP1, November 2020

8.0

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Mozilla Public License 2.0

commercial

free trial 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

Java

C++

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

AIX
Linux
Windows

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

Data scheme

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

SQL

Support of SQL

SQL-like query language

yes

SQL 2003 with some extensions

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC
Proprietary protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

yes, in SQL, C, R

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication available in experimental status

none

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

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

managed by 'Learn by Usage'

yes

User concepts

Access control

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

Specific characteristics

Column-store In-memory optimized GeoSpatial support JSON document support
» more

Competitive advantages

Scalable architecture - vertical data organization and in-memory optimization guarantee...
» more

Typical application scenarios

Analytical database, Data warehouse, OLAP Data mining Scientific database
» more

Key customers

Numascale , Spinque , SecurActive , CHS , NOZHUP
» more

Licensing and pricing models

Free and open-source software, Mozilla Public License 2.0 Commercial support available
» more

News

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11 November 2020

Taking MonetDB/e for a taxi ride
27 October 2020

The MonetDB/e Python interface for data analytics
27 October 2020

MonetDB/e, a mature embedded SQL DBMS
27 October 2020

Faster, robuster and feature richer: MonetDB in 2020 and beyond
19 October 2020

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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