DBMS > Blazegraph vs. Drizzle vs. GridGain vs. Hyprcubd vs. SQLite

System Properties Comparison Blazegraph vs. Drizzle vs. GridGain vs. Hyprcubd vs. SQLite

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.

GridGain is an in-memory computing platform, built on Apache Ignite

Serverless Time Series DBMS

Widely used embeddable, in-process RDBMS

Primary database model

Graph DBMS
RDF store

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

blazegraph.com

www.gridgain.com

hyprcubd.com (offline)

www.sqlite.org

Technical documentation

wiki.blazegraph.com

www.gridgain.com/docs/index.html

www.sqlite.org/docs.html

Developer

Blazegraph

Drizzle project, originally started by Brian Aker

GridGain Systems, Inc.

Hyprcubd, Inc.

Dwayne Richard Hipp

Initial release

2006

2008

2007

2000

Current release

2.1.5, March 2019

7.2.4, September 2012

GridGain 8.5.1

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

extended commercial license available

Open Source

GNU GPL

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java, C++, .Net

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux
OS X
Solaris
Windows

hosted

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

RDF literal types

yes

time, int, uint, float, string

yes

not rigid because of 'dynamic typing' concept.

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

with proprietary extensions

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

JDBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

gRPC (https)

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C
C++
Java
PHP

C#
C++
Java
PHP
Python
Ruby
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

yes (compute grid and cache interceptors can be used instead)

Triggers

hooks for callbacks inside the server can be used.

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

via file-system locks

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

Security Hooks for custom implementations

token access

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