DBMS > Apache Drill vs. Hive vs. Hypertable vs. MariaDB vs. SWC-DB

System Properties Comparison Apache Drill vs. Hive vs. Hypertable vs. MariaDB vs. SWC-DB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

An open source BigTable implementation based on distributed file systems such as Hadoop

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.

A high performance, scalable Wide Column DBMS

Primary database model

Document store
Relational DBMS

Secondary database models

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

Time Series DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	91.04
Rank	#13	Overall
	#9	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

drill.apache.org

hive.apache.org

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

drill.apache.org/docs

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

mariadb.com/kb/en/library

Developer

Apache Software Foundation

initially developed by Facebook

Hypertable Inc.

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

The lead developer Monty Widenius is the original author of MySQL

Alex Kashirin

Initial release

2012

2009

Fork of MySQL, which was first released in 1995

2020

Current release

1.20.3, January 2023

3.1.3, April 2022

0.9.8.11, March 2016

11.3.2, February 2024

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2

Open Source

GNU version 3. Commercial license available

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

GPL V3

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.

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Implementation language

Java

C++

C and C++

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

Dynamic columns are supported

schema-free

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.

yes

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like DML and DDL statements

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Thrift

C++ API
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol
Thrift

Supported programming languages

C++

C++
Java
PHP
Python

C++
Java
Perl
PHP
Python
Ruby

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

C++

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

yes

PL/SQL compatibility added with version 10.3

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

several options for horizontal partitioning and Sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

selectable replication factor on file system level

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

not for in-memory storage engine

yes

In-memory capabilities

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

Depending on the underlying data source

yes

with MEMORY storage engine

User concepts

Access control

Depending on the underlying data source

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

Web, SaaS and Cloud operational applications that require high availability, scalability...
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Key customers

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Market metrics

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Licensing and pricing models

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