DBMS > AlaSQL vs. Altibase vs. Machbase Neo vs. Spark SQL

System Properties Comparison AlaSQL vs. Altibase vs. Machbase Neo vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

An enterprise grade, high-performance RDBMS

TimeSeries DBMS for AIoT and BigData

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

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	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

github.com/ALTIBASE/Documents/tree/master/Manuals

machbase.com/dbms

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Andrey Gershun & Mathias R. Wulff

Altibase

Machbase

Apache Software Foundation

Initial release

2014

1999

2013

2014

Current release

v7.3, 2023, August 2023

V8.0, August 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open source edition discontinued with March 2023

commercial

free test version available

Open Source

Apache 2.0

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++

Scala

Server operating systems

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

AIX
HP-UX
Linux

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

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

yes

SQL

Support of SQL

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

ANSI SQL-92

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

JavaScript API

JDBC
ODBC
Proprietary protocol

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

JDBC
ODBC

Supported programming languages

JavaScript

C
C++
Java

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Java
Python
R
Scala

Server-side scripts

Stored procedures

stored procedures and stored functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

selectable replication factor

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

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