DBMS > Amazon CloudSearch vs. Microsoft SQL Server vs. Weaviate vs. Yaacomo

System Properties Comparison Amazon CloudSearch vs. Microsoft SQL Server vs. Weaviate vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

Microsofts flagship relational DBMS

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

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	1.81
Rank	#137	Overall
	#12	Search engines

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.52
Rank	#153	Overall
	#6	Vector DBMS

Website

aws.amazon.com/cloudsearch

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

github.com/weaviate/weaviate
weaviate.io

yaacomo.com

Technical documentation

docs.aws.amazon.com/cloudsearch

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

weaviate.io/developers/weaviate

Developer

Amazon

Microsoft

Weaviate B.V.

Q2WEB GmbH

Initial release

2012

1989

2019

2009

Current release

SQL Server 2022, November 2022

1.19, May 2023

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

commercial license available with Weaviate Enterprise

commercial

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++

Server operating systems

hosted

Linux
Windows

Android
Linux
Windows

Data scheme

yes

yes, maps to GraphQL interface

yes

Typing

predefined data types such as float or date

yes

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

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

all search fields are automatically indexed

yes

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

yes

SQL

Support of SQL

yes

GraphQL is used as query language

yes

APIs and other access methods

HTTP API

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

GraphQL query language
RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

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

JavaScript / TypeScript
Python

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

yes

automatic partitioning across Amazon Search Instance as required

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

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes, but depending on the SQL-Server Edition

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

In-memory capabilities

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

yes

User concepts

Access control

authentication via encrypted signatures

fine grained access rights according to SQL-standard

API Keys
OpenID Connect Discovery

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more

Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more

Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
» more

Key customers

All companies that have data.
» more

Market metrics

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

Licensing and pricing models

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.