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DBMS > Blazegraph vs. IBM Db2 Event Store vs. RethinkDB vs. SQL.JS

System Properties Comparison Blazegraph vs. IBM Db2 Event Store vs. RethinkDB vs. SQL.JS

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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.

Distributed Event Store optimized for Internet of Things use cases

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Port of SQLite to JavaScript

Primary database model

Graph DBMS
RDF store

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

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

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Website

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

Technical documentation

wiki.blazegraph.com

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

rethinkdb.com/docs

sql.js.org/documentation/index.html

Developer

Blazegraph

IBM

The Linux Foundation

since July 2017

Alon Zakai

enhancements implemented by others

Initial release

2006

2017

2009

2012

Current release

2.1.5, March 2019

2.0

2.4.1, August 2020

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

free developer edition available

Open Source

Apache Version 2

Open Source

Cloud-based only

Only available as a cloud service

no

no

no

no

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C and C++

C++

JavaScript

Server operating systems

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

yes

yes

string, binary, float, bool, date, geometry

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.

no

no

no

Secondary indexes

yes

no

yes

SQL

Support of SQL

SPARQL is used as query language

yes

through the embedded Spark runtime

no

yes

SQL-92 is not fully supported

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JavaScript API

Supported programming languages

.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

C

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

JavaScript

Server-side scripts

Stored procedures

yes

yes

no

Triggers

no

no

Client-side triggers through changefeeds

no

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active-active shard replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

no

no

yes

no

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in Graphs

no

no

yes

Transaction concepts

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

ACID

no

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

MVCC based

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

no

except by serializing a db to a file

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

no

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

yes

users and table-level permissions

no

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