DBMS > HBase vs. HugeGraph vs. SQLite vs. Stardog vs. Transwarp ArgoDB

System Properties Comparison HBase vs. HugeGraph vs. SQLite vs. Stardog vs. Transwarp ArgoDB

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

A fast-speed and highly-scalable Graph DBMS

Widely used embeddable, in-process RDBMS

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Secondary database models

Search engine

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

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Website

hbase.apache.org

github.com/hugegraph
hugegraph.apache.org

www.sqlite.org

www.stardog.com

www.transwarp.cn/en/product/argodb

Technical documentation

hbase.apache.org/book.html

hugegraph.apache.org/docs

www.sqlite.org/docs.html

docs.stardog.com

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

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Baidu

Dwayne Richard Hipp

Stardog-Union

Transwarp

Initial release

2008

2018

2000

2010

Current release

2.3.4, January 2021

0.9

3.46.0 (23 May 2024), May 2024

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2.0

Open Source

Public Domain

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux
macOS
Unix

server-less

Linux
macOS
Windows

Data scheme

schema-free, schema definition possible

yes

dynamic column types

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

not rigid because of 'dynamic typing' concept.

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.

Import/export of XML data possible

Secondary indexes

yes

also supports composite index and range index

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

APIs and other access methods

Java API
RESTful HTTP API
Thrift

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

Groovy
Java
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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

Coprocessors in Java

asynchronous Gremlin script jobs

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

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

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

edges in graph

yes

relationships in graphs

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Users, roles and permissions

Access rights for users and roles

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