DBMS > Blazegraph vs. Drizzle vs. HEAVY.AI vs. Hyprcubd

System Properties Comparison Blazegraph vs. Drizzle vs. HEAVY.AI vs. Hyprcubd

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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.

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Serverless Time Series DBMS

Primary database model

Graph DBMS
RDF store

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.77
Rank	#222	Overall
	#20	Graph DBMS
	#8	RDF stores

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Website

blazegraph.com

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

hyprcubd.com (offline)

Technical documentation

wiki.blazegraph.com

docs.heavy.ai

Developer

Blazegraph

Drizzle project, originally started by Brian Aker

HEAVY.AI, Inc.

Hyprcubd, Inc.

Initial release

2006

2008

2016

Current release

2.1.5, March 2019

7.2.4, September 2012

5.10, January 2022

License

Commercial or Open Source

Open Source

extended commercial license available

Open Source

GNU GPL

Open Source

Apache Version 2; enterprise edition available

commercial

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++

C++ and CUDA

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

yes

time, int, uint, float, string

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

with proprietary extensions

yes

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

JDBC

JDBC
ODBC
Thrift
Vega

gRPC (https)

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C
C++
Java
PHP

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts

Stored procedures

yes

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Multi-source replication

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

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

token access

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More resources

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