DBMS > Axibase vs. Cubrid vs. Graph Engine vs. Microsoft Azure Synapse Analytics

System Properties Comparison Axibase vs. Cubrid vs. Graph Engine vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

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

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

Primary database model

Time Series DBMS

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

axibase.com/docs/atsd/finance

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

www.graphengine.io

azure.microsoft.com/services/synapse-analytics

Technical documentation

cubrid.org/manuals

www.graphengine.io/docs/manual

docs.microsoft.com/azure/synapse-analytics

Developer

Axibase Corporation

CUBRID Corporation, CUBRID Foundation

Microsoft

Initial release

2013

2008

2010

2016

Current release

15585

11.0, January 2021

License

Commercial or Open Source

commercial

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

Open Source

Apache Version 2.0

Open Source

MIT License

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

Java

C, C++, Java

.NET and C

C++

Server operating systems

Linux

Linux
Windows

.NET

hosted

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

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

C#
C++
F#
Visual Basic

C#
Java
PHP

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

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

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