DBMS > Apache IoTDB vs. Geode vs. NCache vs. RDF4J

System Properties Comparison Apache IoTDB vs. Geode vs. NCache vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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.

Primary database model

Time Series DBMS

Key-value store

RDF store

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

iotdb.apache.org

geode.apache.org

www.alachisoft.com/ncache

rdf4j.org

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

geode.apache.org/docs

www.alachisoft.com/resources/docs

rdf4j.org/documentation

Developer

Apache Software Foundation

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Alachisoft

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

Initial release

2018

2002

2005

2004

Current release

1.1.0, April 2023

1.1, February 2017

5.3.3, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Enterprise Edition 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

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Implementation language

Java

C#, .NET, .NET Core, Java

Java

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

the JDK (8 or later) is also required

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL-like query language (OQL)

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

APIs and other access methods

JDBC
Native API

Java Client API
Memcached protocol
RESTful 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

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
All JVM based languages
C++
Groovy
Java
Scala

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

Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

support for stored procedures with SQL-Server CLR

yes

Triggers

yes

Cache Event Listeners

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Multi-source replication

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency

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

Foreign keys

Referential integrity

Transaction concepts

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

yes, on a single node

optimistic locking and pessimistic locking

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

yes

Access rights per client and object definable

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

More information provided by the system vendor

Specific characteristics

NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more

Competitive advantages

NCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more

Typical application scenarios

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more

Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more

Market metrics

Market Leader in .NET Distributed Caching since 2005.
» more

Licensing and pricing models

NCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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

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