DBMS > Graph Engine vs. Microsoft Azure SQL Database vs. Postgres-XL vs. Snowflake vs. Sqrrl

System Properties Comparison Graph Engine vs. Microsoft Azure SQL Database vs. Postgres-XL vs. Snowflake vs. Sqrrl

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

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

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

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Graph DBMS
Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.graphengine.io

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

www.postgres-xl.org

www.snowflake.com

sqrrl.com

Technical documentation

www.graphengine.io/docs/manual

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

www.postgres-xl.org/documentation

docs.snowflake.net/manuals/index.html

Developer

Microsoft

Snowflake Computing Inc.

Amazon

originally Sqrrl Data, Inc.

Initial release

2010

2014

since 2012, originally named StormDB

2014

2012

Current release

V12

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

.NET and C

C++

Java

Server operating systems

.NET

hosted

Linux
macOS

hosted

Linux

Data scheme

yes

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

schema-free

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

XML type, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC

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

CLI Client
JDBC
ODBC

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

C#
C++
F#
Visual Basic

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

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

JavaScript (Node.js)
Python

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

Transact SQL

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with always 3 replicas available

yes

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

MVCC

ACID

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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