DBMS > Amazon Redshift vs. HBase vs. HugeGraph vs. MarkLogic vs. TypeDB

System Properties Comparison Amazon Redshift vs. HBase vs. HugeGraph vs. MarkLogic vs. TypeDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

A fast-speed and highly-scalable Graph DBMS

Operational and transactional Enterprise NoSQL database

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Relational DBMS

Wide column store

Graph DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

aws.amazon.com/redshift

hbase.apache.org

github.com/hugegraph
hugegraph.apache.org

www.marklogic.com

typedb.com

Technical documentation

docs.aws.amazon.com/redshift

hbase.apache.org/book.html

hugegraph.apache.org/docs

docs.marklogic.com

typedb.com/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Baidu

MarkLogic Corp.

Vaticle

Initial release

2012

2008

2018

2001

2016

Current release

2.3.4, January 2021

0.9

11.0, December 2022

2.26.3, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

GPL Version 3, commercial licenses available

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

C++

Java

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

Linux
macOS
Unix

Linux
OS X
Windows

Data scheme

yes

schema-free, schema definition possible

yes

schema-free

Schema can be enforced

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

restricted

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL92

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
Thrift

Java API
RESTful HTTP API
TinkerPop Gremlin

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Groovy
Java
PHP
Python
Scala

Groovy
Java
Python

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Coprocessors in Java

asynchronous Gremlin script jobs

yes

via XQuery or JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

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

yes

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

edges in graph

substituted by the relationship feature

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

can act as a resource manager in an XA/JTA transaction

ACID

Concurrency

Support for concurrent manipulation of data

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

yes, with Range Indexes

User concepts

Access control

fine grained access rights according to SQL-standard

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

Users, roles and permissions

Role-based access control at the document and subdocument levels

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Licensing and pricing models

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