DBMS > AnzoGraph DB vs. Apache Jena - TDB vs. EsgynDB vs. Microsoft SQL Server vs. Percona Server for MongoDB

System Properties Comparison AnzoGraph DB vs. Apache Jena - TDB vs. EsgynDB vs. Microsoft SQL Server vs. Percona Server for MongoDB

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Microsofts flagship relational DBMS

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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

Score	3.75
Rank	#84	Overall
	#3	RDF stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Website

cambridgesemantics.com/anzograph

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

www.esgyn.cn

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

www.percona.com/mongodb/software/percona-server-for-mongodb

Technical documentation

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

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

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

docs.percona.com/percona-distribution-for-mongodb

Developer

Cambridge Semantics

Apache Software Foundation

originally developed by HP Labs

Esgyn

Microsoft

Percona

Initial release

2018

2000

2015

1989

2015

Current release

2.3, January 2021

4.9.0, July 2023

SQL Server 2022, November 2022

3.4.10-2.10, November 2017

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

GPL Version 2

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++, Java

C++

Server operating systems

Linux

All OS with a Java VM

Linux

Linux
Windows

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

yes

RDF Schemas

yes

schema-free

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

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

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

proprietary protocol using JSON

Supported programming languages

C++
Java
Python

Java

All languages supporting JDBC/ODBC/ADO.Net

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

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Java Stored Procedures

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

JavaScript

Triggers

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

Multi-source replication between multi datacenters

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Eventual 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

via In-Memory Engine

User concepts

Access control

Access rights for users and roles

Access control via Jena Security

fine grained access rights according to SQL-standard

Access rights for users and roles

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