DBMS > AnzoGraph DB vs. Kinetica vs. Microsoft SQL Server vs. OpenQM vs. SiriDB

System Properties Comparison AnzoGraph DB vs. Kinetica vs. Microsoft SQL Server vs. OpenQM vs. SiriDB

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Fully vectorized database across both GPUs and CPUs

Microsofts flagship relational DBMS

QpenQM is a high-performance, self-tuning, multi-value DBMS

Open Source Time Series DBMS

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

cambridgesemantics.com/anzograph

www.kinetica.com

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

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

siridb.com

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.kinetica.com

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

docs.siridb.com

Developer

Cambridge Semantics

Kinetica

Microsoft

Rocket Software, originally Martin Phillips

Cesbit

Initial release

2018

2012

1989

1993

2017

Current release

2.3, January 2021

7.1, August 2021

SQL Server 2022, November 2022

3.4-12

License

Commercial or Open Source

commercial

free trial version available

commercial

restricted free version is available

Open Source

GPLv2, extended commercial license available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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Implementation language

C, C++

C++

Server operating systems

Linux

Linux
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

yes

with some exceptions

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like DML and DDL statements

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC
ODBC
RESTful HTTP API

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

HTTP API

Supported programming languages

C++
Java
Python

C++
Java
JavaScript (Node.js)
Python

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

.Net
Basic
C
Java
Objective C
PHP
Python

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

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

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

yes

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

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

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

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

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

yes

User concepts

Access control

Access rights for users and roles

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

simple rights management via user accounts

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