DBMS > Brytlyt vs. IRONdb vs. NCache vs. RDF4J vs. VoltDB

System Properties Comparison Brytlyt vs. IRONdb vs. NCache vs. RDF4J vs. VoltDB

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Open-Source and Enterprise in-memory Key-Value Store

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

brytlyt.io

www.circonus.com/solutions/time-series-database/

www.alachisoft.com/ncache

rdf4j.org

www.voltdb.com

Technical documentation

docs.brytlyt.io

docs.circonus.com/irondb/category/getting-started

www.alachisoft.com/resources/docs

rdf4j.org/documentation

docs.voltdb.com

Developer

Brytlyt

Circonus LLC.

Alachisoft

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

VoltDB Inc.

Initial release

2016

2017

2005

2004

2010

Current release

5.0, August 2023

V0.10.20, January 2018

5.3.3, April 2024

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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 and C++

C#, .NET, .NET Core, Java

Java

Java, C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
Windows

Linux
OS X
Unix
Windows

Linux
OS X

for development

Data scheme

yes

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (Circonus Analytics Query Language: CAQL)

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

only a subset of SQL 99

APIs and other access methods

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

HTTP API

IDistributedCache
JCache
LINQ
Proprietary native API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Java
PHP
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes, in Lua

support for stored procedures with SQL-Server CLR

yes

Java

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

configurable replication factor, datacenter aware

yes, with selectable consistency level

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

ACID

Isolation support depends on the API used

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

Snapshots and command logging

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

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
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Market metrics

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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