DBMS > IBM Db2 warehouse vs. Microsoft Azure Cosmos DB vs. TigerGraph vs. Weaviate

System Properties Comparison IBM Db2 warehouse vs. Microsoft Azure Cosmos DB vs. TigerGraph vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

Cloud-based data warehousing service

Globally distributed, horizontally scalable, multi-model database service

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

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

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Vector DBMS

Secondary database models

Spatial DBMS

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

Score	1.26
Rank	#162	Overall
	#73	Relational DBMS

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.44
Rank	#152	Overall
	#14	Graph DBMS

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

www.ibm.com/products/db2/warehouse

azure.microsoft.com/services/cosmos-db

www.tigergraph.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

learn.microsoft.com/azure/cosmos-db

docs.tigergraph.com

weaviate.io/developers/weaviate

Developer

IBM

Microsoft

Weaviate B.V.

Initial release

2014

2017

2019

Current release

1.19, May 2023

License

Commercial or Open Source

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

hosted

Linux

Data scheme

yes

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.

Import/export of XML data possible

Secondary indexes

yes

All properties auto-indexed by default

yes

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

SQL

Support of SQL

yes

SQL-like query language

SQL-like query language (GSQL)

GraphQL is used as query language

APIs and other access methods

.NET Client API
JDBC
ODBC
OLE DB

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

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

C++
Java

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

PL/SQL, SQL PL

JavaScript

yes

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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

Access rights can be defined down to the item level

Role-based access control

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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