DBMS > Derby vs. Hive vs. Realm vs. SiteWhere

System Properties Comparison Derby vs. Hive vs. Realm vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Document store

Time Series DBMS

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

db.apache.org/derby

hive.apache.org

realm.io

github.com/sitewhere/sitewhere

Technical documentation

db.apache.org/derby/manuals/index.html

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

realm.io/docs

sitewhere1.sitewhere.io/index.html

Developer

Apache Software Foundation

initially developed by Facebook

Realm, acquired by MongoDB in May 2019

SiteWhere

Initial release

1997

2012

2014

2010

Current release

10.17.1.0, November 2023

3.1.3, April 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

All OS with a Java VM

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Data scheme

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC

JDBC
ODBC
Thrift

HTTP REST

Supported programming languages

Java

C++
Java
PHP
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions and integration of map-reduce

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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.

yes

In-Memory realm

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

yes

Users with fine-grained authorization concept

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