DBMS > Badger vs. Hive vs. IBM Cloudant vs. SiteWhere

System Properties Comparison Badger vs. Hive vs. IBM Cloudant vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Database as a Service offering based on Apache CouchDB

M2M integration platform for persisting/querying time series data

Primary database model

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

github.com/dgraph-io/badger

hive.apache.org

www.ibm.com/products/cloudant

github.com/sitewhere/sitewhere

Technical documentation

godoc.org/github.com/dgraph-io/badger

cwiki.apache.org/confluence/display/Hive/Home

cloud.ibm.com/docs/Cloudant

sitewhere1.sitewhere.io/index.html

Developer

DGraph Labs

Apache Software Foundation

initially developed by Facebook

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

SiteWhere

Initial release

2017

2012

2010

Current release

3.1.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2

commercial

Open Source

Common Public Attribution License Version 1.0

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

Java

Erlang

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

predefined scheme

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

APIs and other access methods

JDBC
ODBC
Thrift

RESTful HTTP/JSON API

HTTP REST

Supported programming languages

C++
Java
PHP
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

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.

User concepts

Access control

Access rights for users, groups and roles

Access rights for users can be defined per database

Users with fine-grained authorization concept

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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