DBMS > IBM Cloudant vs. JaguarDB vs. NuoDB vs. Riak TS vs. Splice Machine

System Properties Comparison IBM Cloudant vs. JaguarDB vs. NuoDB vs. Riak TS vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

Performant, highly scalable DBMS for AI and IoT applications

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Document store

Key-value store
Vector DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#15	Vector DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

www.ibm.com/products/cloudant

www.jaguardb.com

www.3ds.com/nuodb-distributed-sql-database

splicemachine.com

Technical documentation

cloud.ibm.com/docs/Cloudant

www.jaguardb.com/support.html

doc.nuodb.com

www.tiot.jp/riak-docs/riak/ts/latest

splicemachine.com/how-it-works

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

DataJaguar, Inc.

Dassault Systèmes

originally NuoDB, Inc.

Open Source, formerly Basho Technologies

Splice Machine

Initial release

2010

2015

2013

2015

2014

Current release

3.3 July 2023

3.0.0, September 2022

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

commercial

limited edition free

Open Source

AGPL 3.0, commercial license available

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++

the server part. Clients available in other languages

C++

Erlang

Java

Server operating systems

hosted

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux
OS X

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

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

restricted

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

yes, limited

yes

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

Java, SQL

Erlang

yes

Java

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

data is dynamically stored/cached on the nodes where it is read/written

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

yes

Managed transparently by NuoDB

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

yes

Transaction concepts

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

atomic operations within a document possible

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

MVCC

yes

yes, multi-version concurrency control (MVCC)

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

Temporary table

yes

User concepts

Access control

Access rights for users can be defined per database

rights management via user accounts

Standard SQL roles/ privileges, Administrative Users

Access rights for users, groups and roles according to SQL-standard

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More resources

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