DBMS > Microsoft SQL Server vs. SAP HANA vs. SQream DB vs. Weaviate

System Properties Comparison Microsoft SQL Server vs. SAP HANA vs. SQream DB vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

In-memory, column based data store. Available as appliance or cloud service

a GPU-based, columnar RDBMS for big data analytics workloads

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

Primary database model

Relational DBMS

Vector DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

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

www.sap.com/products/hana.html

sqream.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

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

help.sap.com/hana

docs.sqream.com

weaviate.io/developers/weaviate

Developer

Microsoft

SAP

SQream Technologies

Weaviate B.V.

Initial release

1989

2010

2017

2019

Current release

SQL Server 2022, November 2022

2.0 SPS07 (April 4, 2023), April 2023

2022.1.6, December 2022

1.19, May 2023

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

commercial license available with Weaviate Enterprise

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux
Windows

Appliance or cloud-service

Linux

Data scheme

yes

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

yes

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

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

SQL

Support of SQL

yes

GraphQL is used as query language

APIs and other access methods

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

JDBC
ODBC

.Net
JDBC
ODBC

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

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

SQLScript, R

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

yes

horizontal and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

yes

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.
» more

Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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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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