DBMS > AlaSQL vs. Amazon Aurora vs. Microsoft Azure Cosmos DB vs. Postgres-XL vs. TigerGraph

System Properties Comparison AlaSQL vs. Amazon Aurora vs. Microsoft Azure Cosmos DB vs. Postgres-XL vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

MySQL and PostgreSQL compatible cloud service by Amazon

Globally distributed, horizontally scalable, multi-model database service

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Graph DBMS

Secondary database models

Document store

Spatial DBMS

Document store
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	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

alasql.org

aws.amazon.com/rds/aurora

azure.microsoft.com/services/cosmos-db

www.postgres-xl.org

www.tigergraph.com

Technical documentation

github.com/AlaSQL/alasql

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

learn.microsoft.com/azure/cosmos-db

www.postgres-xl.org/documentation

docs.tigergraph.com

Developer

Andrey Gershun & Mathias R. Wulff

Amazon

Microsoft

Initial release

2014

2015

2014

since 2012, originally named StormDB

2017

Current release

10 R1, October 2018

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Mozilla public license

commercial

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++

Server operating systems

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

hosted

Linux
macOS

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

XML type, but no XML query functionality

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

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

yes

SQL-like query language

yes

distributed, parallel query execution

SQL-like query language (GSQL)

APIs and other access methods

JavaScript API

ADO.NET
JDBC
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

JavaScript

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java

Server-side scripts

Stored procedures

yes

JavaScript

user defined functions

yes

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Implicit feature of the cloud service

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

MVCC

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Role-based access control

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