DBMS > Amazon Aurora vs. Microsoft SQL Server vs. Sqrrl vs. SwayDB vs. TimescaleDB

System Properties Comparison Amazon Aurora vs. Microsoft SQL Server vs. Sqrrl vs. SwayDB vs. TimescaleDB

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

MySQL and PostgreSQL compatible cloud service by Amazon

Microsofts flagship relational DBMS

Adaptable, secure NoSQL built on Apache Accumulo

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Time Series DBMS

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	8.50
Rank	#49	Overall
	#31	Relational DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	0.04
Rank	#373	Overall
	#57	Key-value stores

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Website

aws.amazon.com/rds/aurora

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

sqrrl.com

swaydb.simer.au

www.timescale.com

Technical documentation

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

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

docs.timescale.com

Developer

Amazon

Microsoft

Amazon

originally Sqrrl Data, Inc.

Simer Plaha

Timescale

Initial release

2015

1989

2012

2018

2017

Current release

SQL Server 2022, November 2022

2.13.0, November 2023

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

GNU Affero GPL V3.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Scala

Server operating systems

hosted

Linux
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

full PostgreSQL SQL syntax

APIs and other access methods

ADO.NET
JDBC
ODBC

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

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

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

Supported programming languages

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

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

Actionscript
C

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

Java
Kotlin
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

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

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

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

Sharding

making use of Hadoop

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, but depending on the SQL-Server Edition

selectable replication factor

making use of Hadoop

none

Source-replica replication with hot standby and reads on replicas

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.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic updates per row, document, or graph entity

Atomic execution of operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

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

fine grained access rights according to SQL-standard

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