DBMS > EsgynDB vs. Microsoft SQL Server vs. Quasardb vs. Riak TS vs. SAP SQL Anywhere

System Properties Comparison EsgynDB vs. Microsoft SQL Server vs. Quasardb vs. Riak TS vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Microsofts flagship relational DBMS

Distributed, high-performance timeseries database

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

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	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	0.19
Rank	#327	Overall
	#30	Time Series DBMS

Score	0.25
Rank	#308	Overall
	#26	Time Series DBMS

Score	4.57
Rank	#78	Overall
	#43	Relational DBMS

Website

www.esgyn.cn

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

quasar.ai

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

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

doc.quasar.ai/master

www.tiot.jp/riak-docs/riak/ts/latest

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Esgyn

Microsoft

quasardb

Open Source, formerly Basho Technologies

SAP

formerly Sybase

Initial release

2015

1989

2009

2015

1992

Current release

SQL Server 2022, November 2022

3.14.1, January 2024

3.0.0, September 2022

17, July 2015

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

C++

Erlang

Server operating systems

Linux

Linux
Windows

BSD
Linux
OS X
Windows

Linux
OS X

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

restricted

yes

SQL

Support of SQL

yes

SQL-like query language

yes, limited

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

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

HTTP API

HTTP API
Native Erlang Interface

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

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

Erlang

yes, in C/C++, Java, .Net or Perl

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

consistent hashing

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes, but depending on the SQL-Server Edition

Source-replica replication with selectable replication factor

selectable replication factor

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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