DBMS > BigObject vs. HyperSQL vs. Oracle NoSQL vs. Realm vs. searchxml

System Properties Comparison BigObject vs. HyperSQL vs. Oracle NoSQL vs. Realm vs. searchxml

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Document store
Key-value store
Relational DBMS

Document store

Native XML DBMS
Search engine

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

bigobject.io

hsqldb.org

www.oracle.com/database/nosql/technologies/nosql

realm.io

www.searchxml.net/category/products

Technical documentation

docs.bigobject.io

hsqldb.org/web/hsqlDocsFrame.html

docs.oracle.com/en/database/other-databases/nosql-database/index.html

realm.io/docs

www.searchxml.net/support/handouts

Developer

BigObject, Inc.

Oracle

Realm, acquired by MongoDB in May 2019

informationpartners gmbh

Initial release

2015

2001

2011

2014

2015

Current release

2.7.2, June 2023

23.3, December 2023

1.0

License

Commercial or Open Source

commercial

free community edition available

Open Source

based on BSD license

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

commercial

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

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
Solaris SPARC/x86

Android
Backend: server-less
iOS
Windows

Windows

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

SQL-like DML and DDL statements

yes

SQL-like DML and DDL statements

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

All languages supporting JDBC/ODBC
Java

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

Lua

Java, SQL

runs within the applications so server-side scripts are unnecessary

yes

on the application server

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

none

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

off heap cache

yes

In-Memory realm

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

yes

Domain, group and role-based access control at the document level and for application services

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