DBMS > AlaSQL vs. Amazon Redshift vs. Oracle NoSQL vs. Sphinx

System Properties Comparison AlaSQL vs. Amazon Redshift vs. Oracle NoSQL vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Large scale data warehouse service for use with business intelligence tools

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

Search engine

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

alasql.org

aws.amazon.com/redshift

www.oracle.com/database/nosql/technologies/nosql

sphinxsearch.com

Technical documentation

github.com/AlaSQL/alasql

docs.aws.amazon.com/redshift

docs.oracle.com/en/database/other-databases/nosql-database/index.html

sphinxsearch.com/docs

Developer

Andrey Gershun & Mathias R. Wulff

Amazon (based on PostgreSQL)

Oracle

Sphinx Technologies Inc.

Initial release

2014

2012

2011

2001

Current release

23.3, December 2023

3.5.1, February 2023

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Java

C++

Server operating systems

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

hosted

Linux
Solaris SPARC/x86

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

optional

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

restricted

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.

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

SQL-like query language (SphinxQL)

APIs and other access methods

JavaScript API

JDBC
ODBC

RESTful HTTP API

Proprietary protocol

Supported programming languages

JavaScript

All languages supporting JDBC/ODBC

C
C#
Go
Java
JavaScript (Node.js)
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

in Python

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

configurable

ACID within a storage node (=shard)

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.

In-memory capabilities

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

yes

off heap cache

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

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