DBMS > AlaSQL vs. JaguarDB vs. Sphinx vs. SWC-DB

System Properties Comparison AlaSQL vs. JaguarDB vs. Sphinx vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Performant, highly scalable DBMS for AI and IoT applications

Open source search engine for searching in data from different sources, e.g. relational databases

A high performance, scalable Wide Column DBMS

Primary database model

Document store
Relational DBMS

Key-value store
Vector DBMS

Search engine

Wide column store

Secondary database models

Time Series DBMS

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

Score	0.42
Rank	#264	Overall
	#42	Document stores
	#122	Relational DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Website

alasql.org

www.jaguardb.com

sphinxsearch.com

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

Technical documentation

github.com/AlaSQL/alasql

www.jaguardb.com/support.html

sphinxsearch.com/docs

Developer

Andrey Gershun & Mathias R. Wulff

DataJaguar, Inc.

Sphinx Technologies Inc.

Alex Kashirin

Initial release

2014

2015

2001

2020

Current release

3.3 July 2023

3.5.1, February 2023

0.5, April 2021

License

Commercial or Open Source

Open Source

MIT-License

Open Source

GPL V3.0

Open Source

GPL version 2, commercial licence available

Open Source

GPL V3

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++

the server part. Clients available in other languages

C++

Server operating systems

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

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

Data scheme

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

full-text index on all search fields

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language (SphinxQL)

SQL-like query language

APIs and other access methods

JavaScript API

JDBC
ODBC

Proprietary protocol

Proprietary protocol
Thrift

Supported programming languages

JavaScript

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C++

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

The original contents of fields are not stored in the Sphinx index.

yes

In-memory capabilities

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

yes

User concepts

Access control

rights management via user accounts

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