DBMS > AlaSQL vs. Axibase vs. Kinetica vs. Microsoft SQL Server vs. Spark SQL

System Properties Comparison AlaSQL vs. Axibase vs. Kinetica vs. Microsoft SQL Server vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Fully vectorized database across both GPUs and CPUs

Microsofts flagship relational DBMS

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

Primary database model

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial 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	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

alasql.org

axibase.com/docs/atsd/finance

www.kinetica.com

www.microsoft.com/en-us/sql-server

spark.apache.org/sql

Technical documentation

github.com/AlaSQL/alasql

docs.kinetica.com

learn.microsoft.com/en-US/sql/sql-server

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

Developer

Andrey Gershun & Mathias R. Wulff

Axibase Corporation

Kinetica

Microsoft

Apache Software Foundation

Initial release

2014

2013

2012

1989

2014

Current release

15585

7.1, August 2021

SQL Server 2022, November 2022

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

MIT-License

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

restricted free version is available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

JavaScript

Java

C, C++

C++

Scala

Server operating systems

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

Linux

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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.

SQL-like query language

SQL-like DML and DDL statements

yes

SQL-like DML and DDL statements

APIs and other access methods

JavaScript API

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC

Supported programming languages

JavaScript

Go
Java
PHP
Python
R
Ruby

C++
Java
JavaScript (Node.js)
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on configuration

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

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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