DBMS > AnzoGraph DB vs. Apache Jena - TDB vs. Microsoft SQL Server vs. Qdrant vs. Sadas Engine

System Properties Comparison AnzoGraph DB vs. Apache Jena - TDB vs. Microsoft SQL Server vs. Qdrant vs. Sadas Engine

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

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

Microsofts flagship relational DBMS

A high-performance vector database with neural network or semantic-based matching

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

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

Score	3.62
Rank	#83	Overall
	#3	RDF stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

cambridgesemantics.com/anzograph

jena.apache.org/documentation/tdb/index.html

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

github.com/qdrant/qdrant
qdrant.tech

www.sadasengine.com

Technical documentation

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

jena.apache.org/documentation/tdb/index.html

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

qdrant.tech/documentation

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Cambridge Semantics

Apache Software Foundation

originally developed by HP Labs

Microsoft

Qdrant

SADAS s.r.l.

Initial release

2018

2000

1989

2021

2006

Current release

2.3, January 2021

4.9.0, July 2023

SQL Server 2022, November 2022

8.0

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache License, Version 2.0

commercial

restricted free version is available

Open Source

Apache Version 2.0

commercial

free trial version available

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Rust

C++

Server operating systems

Linux

All OS with a Java VM

Linux
Windows

Docker
Linux
macOS
Windows

AIX
Linux
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

RDF Schemas

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

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

yes

APIs and other access methods

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

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

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

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

JDBC
ODBC
Proprietary protocol

Supported programming languages

C++
Java
Python

Java

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

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

Triggers

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

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

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

yes, but depending on the SQL-Server Edition

Collection-level replication

none

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

Eventual Consistency, tunable consistency

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

TDB Transactions

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

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users and roles

Access control via Jena Security

fine grained access rights according to SQL-standard

Key-based authentication

Access rights for users, groups and roles according to SQL-standard

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