DBMS > AlaSQL vs. jBASE vs. Netezza vs. Splice Machine

System Properties Comparison AlaSQL vs. jBASE vs. Netezza vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A robust multi-value DBMS comprising development tools and middleware

Data warehouse and analytics appliance part of IBM PureSystems

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

Multivalue DBMS

Relational DBMS

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

Score	0.49
Rank	#259	Overall
	#40	Document stores
	#120	Relational DBMS

Score	1.43
Rank	#160	Overall
	#3	Multivalue DBMS

Score	10.18
Rank	#46	Overall
	#29	Relational DBMS

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Website

alasql.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.ibm.com/products/netezza

splicemachine.com

Technical documentation

github.com/AlaSQL/alasql

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

splicemachine.com/how-it-works

Developer

Andrey Gershun & Mathias R. Wulff

Rocket Software (formerly Zumasys)

IBM

Splice Machine

Initial release

2014

1991

2000

2014

Current release

5.7

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

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)

AIX
Linux
Windows

Linux

included in appliance

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

optional

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.

yes

Secondary indexes

yes

SQL

Support of SQL

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

Embedded SQL for jBASE in BASIC

yes

APIs and other access methods

JavaScript API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

JDBC
ODBC
OLE DB

JDBC
Native Spark Datasource
ODBC

Supported programming languages

JavaScript

.Net
Basic
Jabbascript
Java

C
C++
Fortran
Java
Lua
Perl
Python
R

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

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

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

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

Access rights can be defined down to the item level

Users with fine-grained authorization concept

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

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