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

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

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

A high performance, scalable Wide Column DBMS

A fast and solid embedded Key-value store

Primary database model

Document store
Relational DBMS

Search engine

Wide column store

Key-value store

Secondary database models

Time Series DBMS

Relational DBMS

using the Octo plugin

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	5.97
Rank	#56	Overall
	#5	Search engines

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Score	0.21
Rank	#309	Overall
	#43	Key-value stores

Website

alasql.org

sphinxsearch.com

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

yottadb.com

Technical documentation

github.com/AlaSQL/alasql

sphinxsearch.com/docs

yottadb.com/resources/documentation

Developer

Andrey Gershun & Mathias R. Wulff

Sphinx Technologies Inc.

Alex Kashirin

YottaDB, LLC

Initial release

2014

2001

2020

2001

Current release

3.5.1, February 2023

0.5, April 2021

License

Commercial or Open Source

Open Source

MIT-License

Open Source

GPL version 2, commercial licence available

Open Source

GPL V3

Open Source

AGPL 3.0

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++

Server operating systems

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

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

Docker
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

SQL-like query language (SphinxQL)

SQL-like query language

by using the Octo plugin

APIs and other access methods

JavaScript API

Proprietary protocol

Proprietary protocol
Thrift

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

JavaScript

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C++

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

optimistic locking

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

Users and groups based on OS-security mechanisms

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More resources

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4 February 2013, Paul Andlinger

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