DBMS > Lovefield vs. mSQL vs. Oracle Berkeley DB vs. SWC-DB vs. Warp 10

System Properties Comparison Lovefield vs. mSQL vs. Oracle Berkeley DB vs. SWC-DB vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used in-process key-value store

A high performance, scalable Wide Column DBMS

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Wide column store

Time Series DBMS

Secondary database models

Time Series DBMS

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

google.github.io/lovefield

hughestech.com.au/products/msql

www.oracle.com/database/technologies/related/berkeleydb.html

github.com/kashirin-alex/swc-db
www.swcdb.org

www.warp10.io

Technical documentation

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

docs.oracle.com/cd/E17076_05/html/index.html

www.warp10.io/content/02_Getting_started

Developer

Google

Hughes Technologies

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Alex Kashirin

SenX

Initial release

2014

1994

2020

2015

Current release

2.1.12, February 2017

4.4, October 2021

18.1.40, May 2020

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free licenses can be provided

Open Source

commercial license available

Open Source

GPL V3

Open Source

Apache License 2.0

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

JavaScript

C, Java, C++ (depending on the Berkeley DB edition)

C++

Java

Server operating systems

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

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Linux
OS X
Windows

Data scheme

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.

yes

only with the Berkeley DB XML edition

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

yes

SQL interfaced based on SQLite is available

SQL-like query language

APIs and other access methods

JDBC
ODBC

Proprietary protocol
Thrift

HTTP API
Jupyter
WebSocket

Supported programming languages

JavaScript

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C++

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

Using read-only observers

yes

only for the SQL API

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

Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

based on HBase

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, 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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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