DBMS > AlaSQL vs. Amazon Redshift vs. Amazon SimpleDB vs. Splice Machine

System Properties Comparison AlaSQL vs. Amazon Redshift vs. Amazon SimpleDB vs. Splice Machine

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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

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store

Relational DBMS

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	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

alasql.org

aws.amazon.com/redshift

aws.amazon.com/simpledb

splicemachine.com

Technical documentation

github.com/AlaSQL/alasql

docs.aws.amazon.com/redshift

docs.aws.amazon.com/simpledb

splicemachine.com/how-it-works

Developer

Andrey Gershun & Mathias R. Wulff

Amazon (based on PostgreSQL)

Amazon

Splice Machine

Initial release

2014

2012

2007

2014

Current release

3.1, March 2021

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

AGPL 3.0, commercial license 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

Server operating systems

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

hosted

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

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

restricted

yes

All columns are indexed automatically

yes

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

yes

APIs and other access methods

JavaScript API

JDBC
ODBC

RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

JavaScript

All languages supporting JDBC/ODBC

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding must be implemented in the application

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Concurrent data updates can be detected by the application

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

fine grained access rights according to SQL-standard

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users, groups and roles according to SQL-standard

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