DBMS > AnzoGraph DB vs. Derby vs. Microsoft SQL Server vs. Percona Server for MySQL vs. Valentina Server

System Properties Comparison AnzoGraph DB vs. Derby vs. Microsoft SQL Server vs. Percona Server for MySQL vs. Valentina Server

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Microsofts flagship relational DBMS

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

Object-relational database and reports server

Primary database model

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.27
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	5.30
Rank	#66	Overall
	#36	Relational DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	2.21
Rank	#121	Overall
	#58	Relational DBMS

Score	0.18
Rank	#329	Overall
	#144	Relational DBMS

Website

cambridgesemantics.com/anzograph

db.apache.org/derby

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

www.percona.com/software/mysql-database/percona-server

www.valentina-db.net

Technical documentation

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

db.apache.org/derby/manuals/index.html

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

www.percona.com/downloads/Percona-Server-LATEST

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Cambridge Semantics

Apache Software Foundation

Microsoft

Percona

Paradigma Software

Initial release

2018

1997

1989

2008

1999

Current release

2.3, January 2021

10.17.1.0, November 2023

SQL Server 2022, November 2022

8.0.36-28, 2024

5.7.5

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache version 2

commercial

restricted free version is available

Open Source

GPL version 2

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

C and C++

Server operating systems

Linux

All OS with a Java VM

Linux
Windows

Linux

Linux
OS X
Windows

Data scheme

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

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

JDBC

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

ADO.NET
JDBC
ODBC

ODBC

Supported programming languages

C++
Java
Python

Java

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

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions and aggregates

Java Stored Procedures

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

none

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

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication
XtraDB Cluster

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

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

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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