DBMS > Databend vs. IBM Cloudant vs. IBM Db2 vs. Microsoft Azure Cosmos DB vs. TigerGraph

System Properties Comparison Databend vs. IBM Cloudant vs. IBM Db2 vs. Microsoft Azure Cosmos DB vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Database as a Service offering based on Apache CouchDB

Common in IBM host environments, 2 different versions for host and Windows/Linux

Globally distributed, horizontally scalable, multi-model database service

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

Primary database model

Relational DBMS

Document store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Spatial DBMS

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	125.90
Rank	#9	Overall
	#6	Relational DBMS

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

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

github.com/datafuselabs/databend
www.databend.com

www.ibm.com/products/cloudant

www.ibm.com/products/db2

azure.microsoft.com/services/cosmos-db

www.tigergraph.com

Technical documentation

docs.databend.com

cloud.ibm.com/docs/Cloudant

www.ibm.com/docs/en/db2

learn.microsoft.com/azure/cosmos-db

docs.tigergraph.com

Developer

Databend Labs

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

IBM

Microsoft

Initial release

2021

2010

1983

host version

2014

2017

Current release

1.0.59, April 2023

12.1, October 2016

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free version is available

commercial

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

Rust

Erlang

C and C++

C++

Server operating systems

hosted
Linux
macOS

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

hosted

Linux

Data scheme

yes

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

SQL-like query language

SQL-like query language (GSQL)

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

RESTful HTTP/JSON API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

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

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

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

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

C++
Java

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

JavaScript

yes

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

only with Windows/Unix/Linux Version

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

with separate tools (MQ, InfoSphere)

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

yes

atomic operations within a document possible

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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.

User concepts

Access control

Users with fine-grained authorization concept, user roles

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Role-based access control

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