DBMS > BigObject vs. Cubrid vs. Kinetica vs. Microsoft Azure Synapse Analytics

System Properties Comparison BigObject vs. Cubrid vs. Kinetica vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

Fully vectorized database across both GPUs and CPUs

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Website

bigobject.io

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

www.kinetica.com

azure.microsoft.com/services/synapse-analytics

Technical documentation

docs.bigobject.io

cubrid.org/manuals

docs.kinetica.com

docs.microsoft.com/azure/synapse-analytics

Developer

BigObject, Inc.

CUBRID Corporation, CUBRID Foundation

Kinetica

Microsoft

Initial release

2015

2008

2012

2016

Current release

11.0, January 2021

7.1, August 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2.0

commercial

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, C++

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Windows

Linux

hosted

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

C#
Java
PHP

Server-side scripts

Stored procedures

Lua

Java Stored Procedures

user defined functions

Transact SQL

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

GPU vRAM or System RAM

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

yes

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