DBMS > Cubrid vs. Microsoft Azure Data Explorer vs. Netezza vs. Newts vs. Quasardb

System Properties Comparison Cubrid vs. Microsoft Azure Data Explorer vs. Netezza vs. Newts vs. Quasardb

Editorial information provided by DB-Engines

Name

Description

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

Fully managed big data interactive analytics platform

Data warehouse and analytics appliance part of IBM PureSystems

Time Series DBMS based on Cassandra

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

column oriented

Relational DBMS

Time Series DBMS

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

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

azure.microsoft.com/services/data-explorer

www.ibm.com/products/netezza

opennms.github.io/newts

quasar.ai

Technical documentation

cubrid.org/manuals

docs.microsoft.com/en-us/azure/data-explorer

github.com/OpenNMS/newts/wiki

doc.quasar.ai/master

Developer

CUBRID Corporation, CUBRID Foundation

Microsoft

IBM

OpenNMS Group

quasardb

Initial release

2008

2019

2000

2014

2009

Current release

11.0, January 2021

cloud service with continuous releases

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

Java

C++

Server operating systems

Linux
Windows

hosted

Linux

included in appliance

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

yes

schema-free

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

yes

integer and binary

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

all fields are automatically indexed

yes

with tags

SQL

Support of SQL

yes

Kusto Query Language (KQL), SQL subset

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

JDBC
ODBC
OLE DB

HTTP REST
Java API

HTTP API

Supported programming languages

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

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

C
C++
Fortran
Java
Lua
Perl
Python
R

Java

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

Java Stored Procedures

Yes, possible languages: KQL, Python, R

yes

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

selectable replication factor

based on Cassandra

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

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 using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Azure Active Directory Authentication

Users with fine-grained authorization concept

Cryptographically strong user authentication and audit trail

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