DBMS > Altibase vs. AnzoGraph DB vs. Google BigQuery vs. Linter vs. Microsoft SQL Server

System Properties Comparison Altibase vs. AnzoGraph DB vs. Google BigQuery vs. Linter vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

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

Large scale data warehouse service with append-only tables

RDBMS for high security requirements

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

altibase.com

cambridgesemantics.com/anzograph

cloud.google.com/bigquery

linter.ru

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

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

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

cloud.google.com/bigquery/docs

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

Developer

Altibase

Cambridge Semantics

Google

relex.ru

Microsoft

Initial release

1999

2018

2010

1990

1989

Current release

v7.3, 2023, August 2023

2.3, January 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

free trial version available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

C++

Server operating systems

AIX
HP-UX
Linux

Linux

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
Windows

Data scheme

yes

Schema-free and OWL/RDFS-schema support

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.

yes

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL-92

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

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

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

RESTful HTTP/JSON API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

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

Supported programming languages

C
C++
Java

C++
Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

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

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions and aggregates

user defined functions

in JavaScript

yes

proprietary syntax with the possibility to convert from PL/SQL

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

Automatic sharding

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication in MPP-Cluster

Source-replica replication

yes, but depending on the SQL-Server Edition

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

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

not needed in graphs

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying 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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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