DBMS > IBM Cloudant vs. jBASE vs. Microsoft Azure Cosmos DB vs. RocksDB vs. TigerGraph

System Properties Comparison IBM Cloudant vs. jBASE vs. Microsoft Azure Cosmos DB vs. RocksDB vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

A robust multi-value DBMS comprising development tools and middleware

Globally distributed, horizontally scalable, multi-model database service

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Primary database model

Document store

Multivalue DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	2.73
Rank	#108	Overall
	#20	Document stores

Score	1.43
Rank	#160	Overall
	#3	Multivalue DBMS

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Score	1.83
Rank	#141	Overall
	#13	Graph DBMS

Website

www.ibm.com/products/cloudant

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

azure.microsoft.com/services/cosmos-db

rocksdb.org

www.tigergraph.com

Technical documentation

cloud.ibm.com/docs/Cloudant

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

learn.microsoft.com/azure/cosmos-db

github.com/facebook/rocksdb/wiki

docs.tigergraph.com

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Rocket Software (formerly Zumasys)

Microsoft

Facebook, Inc.

Initial release

2010

1991

2014

2013

2017

Current release

5.7

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

BSD

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

Erlang

C++

Server operating systems

hosted

AIX
Linux
Windows

hosted

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

optional

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.

yes

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

Embedded SQL for jBASE in BASIC

SQL-like query language

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

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

C++ API
Java API

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

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
Basic
Jabbascript
Java

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

C
C++
Go
Java
Perl
Python
Ruby

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

Sharding

Implicit feature of the cloud service

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

yes

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

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

atomic operations within a document possible

ACID

Multi-item ACID transactions with snapshot isolation within a partition

yes

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.

yes

User concepts

Access control

Access rights for users can be defined per database

Access rights can be defined down to the item level

Role-based access control

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