DBMS > Brytlyt vs. Drizzle vs. EsgynDB vs. GigaSpaces vs. RDF4J

System Properties Comparison Brytlyt vs. Drizzle vs. EsgynDB vs. GigaSpaces vs. RDF4J

Editorial information provided by DB-Engines

Name

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

Description

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

RDF store

Secondary database models

Graph DBMS
Search engine

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

Score	0.27
Rank	#292	Overall
	#132	Relational DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	0.91
Rank	#197	Overall
	#33	Document stores
	#7	Object oriented DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

Technical documentation

docs.brytlyt.io

docs.gigaspaces.com/latest/landing.html

rdf4j.org/documentation

Developer

Brytlyt

Drizzle project, originally started by Brian Aker

Esgyn

Gigaspaces Technologies

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2016

2008

2015

2000

2004

Current release

5.0, August 2023

7.2.4, September 2012

15.5, September 2020

License

Commercial or Open Source

commercial

Open Source

GNU GPL

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

Eclipse Distribution License (EDL), v1.0.

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

C, C++ and CUDA

C++

C++, Java

Java, C++, .Net

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux

Linux
macOS
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

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.

yes

specific XML-type available, but no XML query functionality.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-99 for query and DML statements

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC

ADO.NET
JDBC
ODBC

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C
C++
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

.Net
C++
Java
Python
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Java Stored Procedures

yes

Triggers

yes

hooks for callbacks inside the server can be used.

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

Role-based access control

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