DBMS > Apache Impala vs. Cubrid vs. Graph Engine vs. Microsoft SQL Server vs. STSdb

System Properties Comparison Apache Impala vs. Cubrid vs. Graph Engine vs. Microsoft SQL Server vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Microsofts flagship relational DBMS

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Key-value store

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

impala.apache.org

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

www.graphengine.io

www.microsoft.com/en-us/sql-server

github.com/STSSoft/STSdb4

Technical documentation

impala.apache.org/impala-docs.html

cubrid.org/manuals

www.graphengine.io/docs/manual

learn.microsoft.com/en-US/sql/sql-server

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

CUBRID Corporation, CUBRID Foundation

Microsoft

STS Soft SC

Initial release

2013

2008

2010

1989

2011

Current release

4.1.0, June 2022

11.0, January 2021

SQL Server 2022, November 2022

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

MIT License

commercial

restricted free version is available

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

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Implementation language

C++

C, C++, Java

.NET and C

C++

Server operating systems

Linux

Linux
Windows

.NET

Linux
Windows

Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

.NET Client API

Supported programming languages

All languages supporting JDBC/ODBC

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

C#
C++
F#
Visual Basic

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C#
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

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