DBMS > IBM Cloudant vs. Kinetica vs. RDF4J vs. Trafodion

System Properties Comparison IBM Cloudant vs. Kinetica vs. RDF4J vs. Trafodion

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Database as a Service offering based on Apache CouchDB

Fully vectorized database across both GPUs and CPUs

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

Transactional SQL-on-Hadoop DBMS

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

www.ibm.com/products/cloudant

www.kinetica.com

rdf4j.org

trafodion.apache.org

Technical documentation

cloud.ibm.com/docs/Cloudant

docs.kinetica.com

rdf4j.org/documentation

trafodion.apache.org/documentation.html

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Kinetica

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

Apache Software Foundation, originally developed by HP

Initial release

2010

2012

2004

2014

Current release

7.1, August 2021

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache 2.0

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

Erlang

C, C++

Java

C++, Java

Server operating systems

hosted

Linux

Linux
OS X
Unix
Windows

Linux

Data scheme

schema-free

yes

RDF Schemas

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET
JDBC
ODBC

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

C++
Java
JavaScript (Node.js)
Python

Java
PHP
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

user defined functions

yes

Java Stored Procedures

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a document possible

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

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

yes

GPU vRAM or System RAM

User concepts

Access control

Access rights for users can be defined per database

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Cloudant Best (and Worst) Practices — Part 1
18 March 2019, IBM

Intro to Enterprise Cloud Storage: How to Set Up a Cloudant Database
1 December 2014, Linux.com

IBM Expands Cloud Database Services with Kubernetes
26 September 2019, EnterpriseAI

IBM to Purchase Cloudant Database as a service (DBaaS) Provider
22 March 2014, App Developer Magazine

IBM Code Engine and IBM Cloudant: Serverless Data and Infrastructure
16 August 2021, IBM

provided by Google News

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Kinetica Delivers Real-Time Vector Similarity Search
20 March 2024, Datanami

Kinetica Delivers Real-Time Vector Similarity Search
22 March 2024, Geospatial World

provided by Google News

GraphDB Goes Open Source
27 January 2020, iProgrammer

provided by Google News

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

provided by Google News

Share this page