DBMS > Microsoft SQL Server vs. Quasardb vs. SpaceTime vs. Sphinx vs. Transwarp KunDB

System Properties Comparison Microsoft SQL Server vs. Quasardb vs. SpaceTime vs. Sphinx vs. Transwarp KunDB

Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

Distributed, high-performance timeseries database

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Open source search engine for searching in data from different sources, e.g. relational databases

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

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

quasar.ai

www.mireo.com/spacetime

sphinxsearch.com

www.transwarp.cn/en/product/kundb

Technical documentation

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

doc.quasar.ai/master

sphinxsearch.com/docs

Developer

Microsoft

quasardb

Mireo

Sphinx Technologies Inc.

Transwarp

Initial release

1989

2009

2020

2001

Current release

SQL Server 2022, November 2022

3.14.1, January 2024

3.5.1, February 2023

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

commercial

Open Source

GPL version 2, commercial licence available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux
Windows

BSD
Linux
OS X
Windows

Linux

FreeBSD
Linux
NetBSD
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

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL-like query language

A subset of ANSI SQL is implemented

SQL-like query language (SphinxQL)

yes

APIs and other access methods

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

HTTP API

RESTful HTTP API

Proprietary protocol

Supported programming languages

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

C#
C++
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

consistent hashing

Fixed-grid hypercubes

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

Source-replica replication with selectable replication factor

Real-time block device replication (DRBD)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

The original contents of fields are not stored in the Sphinx index.

yes

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

yes

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