DBMS > Hazelcast vs. Lovefield vs. mSQL vs. RavenDB vs. SQLite

System Properties Comparison Hazelcast vs. Lovefield vs. mSQL vs. RavenDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

Embeddable relational database for web apps written in pure JavaScript

mSQL (Mini SQL) is a simple and lightweight RDBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

hazelcast.com

google.github.io/lovefield

hughestech.com.au/products/msql

ravendb.net

www.sqlite.org

Technical documentation

hazelcast.org/imdg/docs

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

ravendb.net/docs

www.sqlite.org/docs.html

Developer

Hazelcast

Google

Hughes Technologies

Hibernating Rhinos

Dwayne Richard Hipp

Initial release

2008

2014

1994

2010

2000

Current release

5.3.6, November 2023

2.1.12, February 2017

4.4, October 2021

5.4, July 2022

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

commercial

free licenses can be provided

Open Source

AGPL version 3, commercial license available

Open Source

Public Domain

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

JavaScript

Server operating systems

All OS with a Java VM

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

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
macOS
Raspberry Pi
Windows

server-less

Data scheme

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language (RQL)

yes

SQL-92 is not fully supported

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

JavaScript

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

Triggers

yes

Events

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

none

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

none

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

ACID

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

yes

User concepts

Access control

Role-based access control

Authorization levels configured per client per database

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