DBMS > HugeGraph vs. IBM Cloudant vs. Kinetica vs. Transwarp ArgoDB

System Properties Comparison HugeGraph vs. IBM Cloudant vs. Kinetica vs. Transwarp ArgoDB

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Database as a Service offering based on Apache CouchDB

Fully vectorized database across both GPUs and CPUs

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Graph DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Search engine

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

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

www.ibm.com/products/cloudant

www.kinetica.com

www.transwarp.cn/en/product/argodb

Technical documentation

hugegraph.apache.org/docs

cloud.ibm.com/docs/Cloudant

docs.kinetica.com

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

Baidu

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Kinetica

Transwarp

Initial release

2018

2010

2012

Current release

0.9

7.1, August 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

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

Java

Erlang

C, C++

Server operating systems

Linux
macOS
Unix

hosted

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

Supported programming languages

Groovy
Java
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

View functions (Map-Reduce) in JavaScript

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

atomic operations within a document possible

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

GPU vRAM or System RAM

User concepts

Access control

Users, roles and permissions

Access rights for users can be defined per database

Access rights for users and roles on table level

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More resources

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