DBMS > AnzoGraph DB vs. Blazegraph vs. IBM Db2 Event Store vs. Ingres vs. MySQL

System Properties Comparison AnzoGraph DB vs. Blazegraph vs. IBM Db2 Event Store vs. Ingres vs. MySQL

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

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

Distributed Event Store optimized for Internet of Things use cases

Well established RDBMS

Widely used open source RDBMS

Primary database model

Graph DBMS
RDF store

Event Store
Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
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	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

cambridgesemantics.com/anzograph

blazegraph.com

www.ibm.com/products/db2-event-store

www.actian.com/databases/ingres

www.mysql.com

Technical documentation

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

wiki.blazegraph.com

www.ibm.com/docs/en/db2-event-store

docs.actian.com/ingres

dev.mysql.com/doc

Developer

Cambridge Semantics

Blazegraph

IBM

Actian Corporation

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2018

2006

2017

1974

originally developed at University Berkely in early 1970s

1995

Current release

2.3, January 2021

2.1.5, March 2019

2.0

11.2, May 2022

8.4.0, April 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

extended commercial license available

commercial

free developer edition available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

Server operating systems

Linux

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

SQL

Support of SQL

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

SPARQL is used as query language

yes

through the embedded Spark runtime

yes

with proprietary extensions

APIs and other access methods

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

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C++
Java
Python

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

Active-active shard replication

Ingres Replicator

Multi-source replication
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 or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Relationships in Graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

MVCC

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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