DBMS > Blazegraph vs. HEAVY.AI vs. IBM Db2 Event Store vs. SiriDB

System Properties Comparison Blazegraph vs. HEAVY.AI vs. IBM Db2 Event Store vs. SiriDB

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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.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Distributed Event Store optimized for Internet of Things use cases

Open Source Time Series DBMS

Primary database model

Graph DBMS
RDF store

Relational DBMS

Event Store
Time Series DBMS

Time Series DBMS

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	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

blazegraph.com

github.com/heavyai/heavydb
www.heavy.ai

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

siridb.com

Technical documentation

wiki.blazegraph.com

docs.heavy.ai

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

docs.siridb.com

Developer

Blazegraph

HEAVY.AI, Inc.

IBM

Cesbit

Initial release

2006

2016

2017

Current release

2.1.5, March 2019

5.10, January 2022

2.0

License

Commercial or Open Source

Open Source

extended commercial license available

Open Source

Apache Version 2; enterprise edition available

commercial

free developer edition available

Open Source

MIT License

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++ and CUDA

C and C++

Server operating systems

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

yes

Numeric data

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.

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

through the embedded Spark runtime

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

JDBC
ODBC
Thrift
Vega

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Active-active shard replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

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

No - written data is immutable

yes

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

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

fine grained access rights according to SQL-standard

simple rights management via user accounts

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More resources

Recent citations in the news

Video: Blazegraph Accelerates Graph Computing with GPUs
20 December 2015, insideHPC

Harnessing GPUs Delivers a Big Speedup for Graph Analytics
15 December 2015, Datanami

This AI Paper Introduces A Comprehensive RDF Dataset With Over 26 Billion Triples Covering Scholarly Data Across All Scientific Disciplines
19 August 2023, MarkTechPost

provided by Google News

Dr. Mike Flaxman, VP or Product Management at HEAVY.AI – Interview Series
19 September 2024, Unite.AI

5 Q’s for Mike Flaxman, Vice President of Heavy.AI
15 August 2024, Center for Data Innovation

HEAVY.AI Accelerates Big Data Analytics with Vultr's High-Performance GPU Cloud Infrastructure
11 September 2024, insideBIGDATA

HEAVY.AI Accelerates Big Data Analytics with Vultr’s High-Performance GPU Cloud Infrastructure
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24 April 2024, SiliconANGLE News

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Mudhakar Srivatsa
11 December 2023, IBM Research

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19 September 2019, Express Computer

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3 June 2019, Datanami

provided by Google News

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