DBMS > AnzoGraph DB vs. Citus vs. Immudb vs. Microsoft SQL Server vs. Transbase

System Properties Comparison AnzoGraph DB vs. Citus vs. Immudb vs. Microsoft SQL Server vs. Transbase

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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Microsofts flagship relational DBMS

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Document store

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.22
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	2.13
Rank	#117	Overall
	#56	Relational DBMS

Score	0.24
Rank	#295	Overall
	#42	Key-value stores

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.citusdata.com

github.com/codenotary/immudb
immudb.io

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

www.transaction.de/en/products/transbase.html

Technical documentation

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

docs.citusdata.com

docs.immudb.io

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

www.transaction.de/en/products/transbase/features.html

Developer

Cambridge Semantics

Codenotary

Microsoft

Transaction Software GmbH

Initial release

2018

2010

2020

1989

1987

Current release

2.3, January 2021

8.1, December 2018

1.2.3, April 2022

SQL Server 2022, November 2022

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

free development license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

Server operating systems

Linux

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

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

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

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

yes

standard, with numerous extensions

SQL-like syntax

yes

APIs and other access methods

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

gRPC protocol
PostgreSQL wire protocol

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

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C++
Java
Python

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
Go
Java
JavaScript (Node.js)
Python

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

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

yes

Triggers

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

other methods possible by using 3rd party extensions

yes, but depending on the SQL-Server Edition

Source-replica replication

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

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

yes

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

Access rights for users and roles

fine grained access rights according to SQL-standard

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