DBMS > Alibaba Cloud Table Store vs. Hive vs. IRONdb vs. MariaDB vs. RDF4J

System Properties Comparison Alibaba Cloud Table Store vs. Hive vs. IRONdb vs. MariaDB vs. RDF4J

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Secondary database models

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

www.alibabacloud.com/product/table-store

hive.apache.org

www.circonus.com/solutions/time-series-database/

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

rdf4j.org

Technical documentation

www.alibabacloud.com/help/en/tablestore

cwiki.apache.org/confluence/display/Hive/Home

docs.circonus.com/irondb/category/getting-started

mariadb.com/kb/en/library

rdf4j.org/documentation

Developer

Alibaba

Apache Software Foundation

initially developed by Facebook

Circonus LLC.

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2016

2012

2017

2009

Fork of MySQL, which was first released in 1995

2004

Current release

3.1.3, April 2022

V0.10.20, January 2018

11.3.2, February 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

Eclipse Distribution License (EDL), v1.0.

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 and C++

Java

Server operating systems

hosted

All OS with a Java VM

Linux

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

schema-free

yes

Dynamic columns are supported

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

with proprietary extensions

APIs and other access methods

HTTP API

JDBC
ODBC
Thrift

HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java
Python

C++
Java
PHP
Python

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Ada
C
C#
C++
D
Eiffel
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes, in Lua

yes

PL/SQL compatibility added with version 10.3

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Automatic, metric affinity per node

several options for horizontal partitioning and Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

configurable replication factor, datacenter aware

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic single-row operations

ACID

not for MyISAM storage engine

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

not for in-memory storage engine

yes

in-memory storage is supported as well

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

with MEMORY storage engine

User concepts

Access control

Access rights based on subaccounts and tokens

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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