DBMS > Apache IoTDB vs. IBM Cloudant vs. NSDb vs. Oracle Berkeley DB

System Properties Comparison Apache IoTDB vs. IBM Cloudant vs. NSDb vs. Oracle Berkeley DB

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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

Database as a Service offering based on Apache CouchDB

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Widely used in-process key-value store

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Website

iotdb.apache.org

www.ibm.com/products/cloudant

nsdb.io

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

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

cloud.ibm.com/docs/Cloudant

nsdb.io/Architecture

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Apache Software Foundation

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2018

2010

2017

1994

Current release

1.1.0, April 2023

18.1.40, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

Open Source

commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Erlang

Java, Scala

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

All OS with a Java VM (>= 1.8)

hosted

Linux
macOS

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

only with the Berkeley DB XML edition

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

SQL interfaced based on SQLite is available

APIs and other access methods

JDBC
Native API

RESTful HTTP/JSON API

gRPC
HTTP REST
WebSocket

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C#
Java
JavaScript
Objective-C
PHP
Ruby

Java
Scala

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

yes

View functions (Map-Reduce) in JavaScript

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

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
Source-replica replication

Source-replica replication

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

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

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 for users can be defined per database

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