DBMS > AlaSQL vs. Graph Engine vs. Sphinx vs. SwayDB

System Properties Comparison AlaSQL vs. Graph Engine vs. Sphinx vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store
Relational DBMS

Graph DBMS
Key-value store

Search engine

Key-value store

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

Technical documentation

github.com/AlaSQL/alasql

www.graphengine.io/docs/manual

sphinxsearch.com/docs

Developer

Andrey Gershun & Mathias R. Wulff

Microsoft

Sphinx Technologies Inc.

Simer Plaha

Initial release

2014

2010

2001

2018

Current release

3.5.1, February 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

MIT License

Open Source

GPL version 2, commercial licence available

Open Source

GNU Affero GPL V3.0

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

.NET and C

C++

Scala

Server operating systems

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

.NET

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

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.

SQL-like query language (SphinxQL)

APIs and other access methods

JavaScript API

RESTful HTTP API

Proprietary protocol

Supported programming languages

JavaScript

C#
C++
F#
Visual Basic

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

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More resources

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