DBMS > FeatureBase vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. TigerGraph vs. Valentina Server

System Properties Comparison FeatureBase vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. TigerGraph vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Database as a Service offering based on Apache CouchDB

Globally distributed, horizontally scalable, multi-model database service

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

Object-relational database and reports server

Primary database model

Relational DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

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

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

www.featurebase.com

www.ibm.com/products/cloudant

azure.microsoft.com/services/cosmos-db

www.tigergraph.com

www.valentina-db.net

Technical documentation

docs.featurebase.com

cloud.ibm.com/docs/Cloudant

learn.microsoft.com/azure/cosmos-db

docs.tigergraph.com

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Molecula and Pilosa Open Source Contributors

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

Paradigma Software

Initial release

2017

2010

2014

2017

1999

Current release

2022, May 2022

5.7.5

License

Commercial or Open Source

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

Erlang

C++

Server operating systems

Linux
macOS

hosted

Linux

Linux
OS X
Windows

Data scheme

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

yes

SQL

Support of SQL

SQL queries

SQL-like query language

SQL-like query language (GSQL)

yes

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

RESTful HTTP/JSON API

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

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

ODBC

Supported programming languages

Java
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

C++
Java

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

JavaScript

yes

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

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

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

yes

Transaction concepts

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

yes

atomic operations within a document possible

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, using Linux fsync

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

fine grained access rights according to SQL-standard

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