DBMS > AlaSQL vs. Microsoft Azure SQL Database vs. Snowflake vs. Splice Machine vs. Stardog

System Properties Comparison AlaSQL vs. Microsoft Azure SQL Database vs. Snowflake vs. Splice Machine vs. Stardog

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Database as a Service offering with high compatibility to Microsoft SQL Server

Cloud-based data warehousing service for structured and semi-structured data

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Document store
Relational DBMS

Relational DBMS

Graph DBMS
RDF store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

alasql.org

azure.microsoft.com/en-us/products/azure-sql/database

www.snowflake.com

splicemachine.com

www.stardog.com

Technical documentation

github.com/AlaSQL/alasql

docs.microsoft.com/en-us/azure/azure-sql

docs.snowflake.net/manuals/index.html

splicemachine.com/how-it-works

docs.stardog.com

Developer

Andrey Gershun & Mathias R. Wulff

Microsoft

Snowflake Computing Inc.

Splice Machine

Stardog-Union

Initial release

2014

2010

2014

2010

Current release

V12

3.1, March 2021

7.3.0, May 2020

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

AGPL 3.0, commercial license available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

C++

Java

Server operating systems

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

hosted

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

schema-free and OWL/RDFS-schema support

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.

yes

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

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

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JavaScript API

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

JavaScript

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript (Node.js)
Python

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

Transact SQL

user defined functions

yes

Java

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

similar concept for controling cloud resources

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with always 3 replicas available

yes

Multi-source replication
Source-replica replication

Multi-source replication in HA-Cluster

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

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

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)

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

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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

Access rights for users and roles

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