DBMS > HugeGraph vs. IBM Cloudant vs. Immudb vs. Kinetica vs. SQLite

System Properties Comparison HugeGraph vs. IBM Cloudant vs. Immudb vs. Kinetica vs. SQLite

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

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Fully vectorized database across both GPUs and CPUs

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Relational DBMS

Spatial DBMS
Time Series DBMS

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.24
Rank	#305	Overall
	#43	Key-value stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

www.ibm.com/products/cloudant

github.com/codenotary/immudb
immudb.io

www.kinetica.com

www.sqlite.org

Technical documentation

hugegraph.apache.org/docs

cloud.ibm.com/docs/Cloudant

docs.immudb.io

docs.kinetica.com

www.sqlite.org/docs.html

Developer

Baidu

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Codenotary

Kinetica

Dwayne Richard Hipp

Initial release

2018

2010

2020

2012

2000

Current release

0.9

1.2.3, April 2022

7.1, August 2021

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Public Domain

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

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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 syntax

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

RESTful HTTP/JSON API

gRPC protocol
PostgreSQL wire protocol

JDBC
ODBC
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Groovy
Java
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
Go
Java
JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

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

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

Sharding

none

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

none

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

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

via file-system locks

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

yes

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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