DBMS > AlaSQL vs. Axibase vs. Microsoft SQL Server vs. Spark SQL vs. Splice Machine

System Properties Comparison AlaSQL vs. Axibase vs. Microsoft SQL Server vs. Spark SQL vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

Microsofts flagship relational DBMS

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

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

Time Series DBMS

Relational DBMS

Secondary database models

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	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

alasql.org

axibase.com/docs/atsd/finance

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

spark.apache.org/sql

splicemachine.com

Technical documentation

github.com/AlaSQL/alasql

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

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

splicemachine.com/how-it-works

Developer

Andrey Gershun & Mathias R. Wulff

Axibase Corporation

Microsoft

Apache Software Foundation

Splice Machine

Initial release

2014

2013

1989

2014

Current release

15585

SQL Server 2022, November 2022

3.5.0 ( 2.13), September 2023

3.1, March 2021

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

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

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Implementation language

JavaScript

Java

C++

Scala

Java

Server operating systems

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

Linux

Linux
Windows

Linux
OS X
Windows

Linux
OS X
Solaris
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

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JavaScript API

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

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

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Supported programming languages

JavaScript

Go
Java
PHP
Python
R
Ruby

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

Java
Python
R
Scala

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

Server-side scripts

Stored procedures

yes

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

yes

Java

Triggers

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

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes, but depending on the SQL-Server Edition

none

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

fine grained access rights according to SQL-standard

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

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