DBMS > Microsoft Azure Cosmos DB vs. MySQL vs. Teradata vs. Weaviate

System Properties Comparison Microsoft Azure Cosmos DB vs. MySQL vs. Teradata vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

Widely used open source RDBMS

A hybrid cloud data analytics software platform (Teradata Vantage)

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

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Vector DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	1.52
Rank	#153	Overall
	#5	Vector DBMS

Website

azure.microsoft.com/services/cosmos-db

www.mysql.com

www.teradata.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

learn.microsoft.com/azure/cosmos-db

dev.mysql.com/doc

docs.teradata.com

weaviate.io/developers/weaviate

Developer

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Teradata

Weaviate B.V.

Initial release

2014

1995

1984

2019

Current release

8.4.0, April 2024

Teradata Vantage 1.0 MU2, January 2019

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

commercial license available with Weaviate Enterprise

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 and C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

hosted
Linux

Data scheme

schema-free

yes

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

JSON 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 properties auto-indexed by default

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

yes

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

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

SQL 2016 + extensions

GraphQL is used as query language

APIs and other access methods

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

JavaScript

yes

proprietary syntax

yes

UDFs, stored procedures, table functions in parallel

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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

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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