DBMS > Blazegraph vs. H2 vs. Microsoft Azure Synapse Analytics vs. Percona Server for MongoDB vs. Stardog

System Properties Comparison Blazegraph vs. H2 vs. Microsoft Azure Synapse Analytics vs. Percona Server for MongoDB vs. Stardog

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.74
Rank	#217	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	0.50
Rank	#250	Overall
	#39	Document stores

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Website

blazegraph.com

www.h2database.com

azure.microsoft.com/services/synapse-analytics

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

www.stardog.com

Technical documentation

wiki.blazegraph.com

www.h2database.com/html/main.html

docs.microsoft.com/azure/synapse-analytics

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

docs.stardog.com

Developer

Blazegraph

Thomas Mueller

Microsoft

Percona

Stardog-Union

Initial release

2006

2005

2016

2015

2010

Current release

2.1.5, March 2019

2.2.220, July 2023

3.4.10-2.10, November 2017

7.3.0, May 2020

License

Commercial or Open Source

Open Source

extended commercial license available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

GPL Version 2

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

hosted

Linux

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

RDF literal types

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SPARQL is used as query language

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

JDBC
ODBC

ADO.NET
JDBC
ODBC

proprietary protocol using JSON

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Java

C#
Java
PHP

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

Transact SQL

JavaScript

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding, horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

Source-replica replication

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

yes

User concepts

Access control

Security and Authentication via Web Application Container (Tomcat, Jetty)

fine grained access rights according to SQL-standard

yes

Access rights for users and roles

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More resources

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