DBMS > Cubrid vs. Microsoft Azure Synapse Analytics vs. SQLite vs. Teradata Aster vs. TerminusDB

System Properties Comparison Cubrid vs. Microsoft Azure Synapse Analytics vs. SQLite vs. Teradata Aster vs. TerminusDB

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Widely used embeddable, in-process RDBMS

Platform for big data analytics on multistructured data sources and types

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

cubrid.com (korean)
cubrid.org (english)

azure.microsoft.com/services/synapse-analytics

www.sqlite.org

terminusdb.com

Technical documentation

cubrid.org/manuals

docs.microsoft.com/azure/synapse-analytics

www.sqlite.org/docs.html

terminusdb.github.io/terminusdb/#

Developer

CUBRID Corporation, CUBRID Foundation

Microsoft

Dwayne Richard Hipp

Teradata

DataChemist Ltd.

Initial release

2008

2016

2000

2005

2018

Current release

11.0, January 2021

3.46.0 (23 May 2024), May 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Public Domain

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Java

C++

Prolog, Rust

Server operating systems

Linux
Windows

hosted

server-less

Linux

Data scheme

yes

dynamic column types

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

yes

SQL-like query language (WOQL)

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC
OLE DB

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

C#
Java
PHP

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C#
C++
Java
Python
R

JavaScript
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Transact SQL

R packages

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

none

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

in-memory journaling

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

Role-based access control

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