DBMS > HyperSQL vs. IBM Cloudant vs. Lovefield vs. Newts

System Properties Comparison HyperSQL vs. IBM Cloudant vs. Lovefield vs. Newts

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Editorial information provided by DB-Engines

Name

Description

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Database as a Service offering based on Apache CouchDB

Embeddable relational database for web apps written in pure JavaScript

Time Series DBMS based on Cassandra

Primary database model

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

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

hsqldb.org

www.ibm.com/products/cloudant

google.github.io/lovefield

opennms.github.io/newts

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

cloud.ibm.com/docs/Cloudant

github.com/google/lovefield/blob/master/docs/spec_index.md

github.com/OpenNMS/newts/wiki

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Google

OpenNMS Group

Initial release

2001

2010

2014

Current release

2.7.2, June 2023

2.1.12, February 2017

License

Commercial or Open Source

Open Source

based on BSD license

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

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

JavaScript

Java

Server operating systems

All OS with a Java VM

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

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

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

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP/JSON API

HTTP REST
Java API

Supported programming languages

All languages supporting JDBC/ODBC
Java

C#
Java
JavaScript
Objective-C
PHP
Ruby

JavaScript

Java

Server-side scripts

Stored procedures

Java, SQL

View functions (Map-Reduce) in JavaScript

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

none

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

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