DBMS > MonetDB vs. Oracle vs. TimescaleDB vs. TypeDB

System Properties Comparison MonetDB vs. Oracle vs. TimescaleDB vs. TypeDB

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Editorial information provided by DB-Engines

Name

Description

A relational database management system that stores data in columns

Widely used RDBMS

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

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Relational DBMS

Time Series DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Relational DBMS

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

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

www.monetdb.org

www.oracle.com/database

www.timescale.com

typedb.com

Technical documentation

www.monetdb.org/Documentation

docs.oracle.com/en/database

docs.timescale.com

typedb.com/docs

Developer

MonetDB BV

Oracle

Timescale

Vaticle

Initial release

2004

1980

2017

2016

Current release

Dec2023 (11.49), December 2023

23c, September 2023

2.15.0, May 2024

2.26.3, January 2024

License

Commercial or Open Source

Open Source

Mozilla Public License 2.0

commercial

restricted free version is available

Open Source

Apache 2.0

Open Source

GPL Version 3, commercial licenses available

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++

Java

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Windows

Data scheme

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

yes

with proprietary extensions

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

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

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

yes, in SQL, C, R

PL/SQL

also stored procedures in Java possible

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

Partitioning methods

Methods for storing different data on different nodes

Sharding via remote tables

Sharding, horizontal partitioning

yes, across time and space (hash partitioning) attributes

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

Multi-source replication
Source-replica replication

Source-replica replication with hot standby and reads on replicas

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

substituted by the relationship feature

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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