DBMS > Microsoft SQL Server vs. mSQL vs. SiteWhere vs. Weaviate vs. XTDB

System Properties Comparison Microsoft SQL Server vs. mSQL vs. SiteWhere vs. Weaviate vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

M2M integration platform for persisting/querying time series data

An AI-native realtime vector database engine that integrates scalable machine learning models.

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	1.52
Rank	#153	Overall
	#5	Vector DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

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

hughestech.com.au/products/msql

github.com/sitewhere/sitewhere

github.com/weaviate/weaviate
weaviate.io

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

sitewhere1.sitewhere.io/index.html

weaviate.io/developers/weaviate

www.xtdb.com/docs

Developer

Microsoft

Hughes Technologies

SiteWhere

Weaviate B.V.

Juxt Ltd.

Initial release

1989

1994

2010

2019

Current release

SQL Server 2022, November 2022

4.4, October 2021

1.19, May 2023

1.19, September 2021

License

Commercial or Open Source

commercial

restricted free version is available

commercial

free licenses can be provided

Open Source

Common Public Attribution License Version 1.0

Open Source

commercial license available with Weaviate Enterprise

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Clojure

Server operating systems

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

predefined scheme

yes, maps to GraphQL interface

schema-free

Typing

predefined data types such as float or date

yes

string, int, float, geo point, date, cross reference, fuzzy references

yes, extensible-data-notation format

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

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

GraphQL is used as query language

limited SQL, making use of Apache Calcite

APIs and other access methods

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

JDBC
ODBC

HTTP REST

GraphQL query language
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

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

C
C++
Delphi
Java
Perl
PHP
Tcl

JavaScript / TypeScript
Python

Clojure
Java

Server-side scripts

Stored procedures

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

based on HBase

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

none

selectable replication factor

based on HBase

yes

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Eventual 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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
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Key customers

All companies that have data.
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Market metrics

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Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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