DBMS > Apache Impala vs. Apache IoTDB vs. MariaDB vs. TimescaleDB

System Properties Comparison Apache Impala vs. Apache IoTDB vs. MariaDB vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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 time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Secondary database models

Document store

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

Relational DBMS

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	1.19
Rank	#176	Overall
	#15	Time Series DBMS

Score	93.81
Rank	#13	Overall
	#9	Relational DBMS

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Website

impala.apache.org

iotdb.apache.org

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

www.timescale.com

Technical documentation

impala.apache.org/impala-docs.html

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

mariadb.com/kb/en/library

docs.timescale.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

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

The lead developer Monty Widenius is the original author of MySQL

Timescale

Initial release

2013

2018

2009

Fork of MySQL, which was first released in 1995

2017

Current release

4.1.0, June 2022

1.1.0, April 2023

11.3.2, February 2024

2.13.0, November 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C and C++

Server operating systems

Linux

All OS with a Java VM (>= 1.8)

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux
OS X
Windows

Data scheme

yes

Dynamic columns are supported

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

with proprietary extensions

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
ODBC

JDBC
Native API

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Java
Python
Scala

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

PL/SQL compatibility added with version 10.3

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

several options for horizontal partitioning and Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Multi-source replication
Source-replica replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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.

yes

with MEMORY storage engine

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

MariaDB is the most powerful open source relational database – modern SQL and JSON...
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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

Deutsche Bank, DBS Bank, Nasdaq, Red Hat, ServiceNow, Verizon and Walgreens Featured...
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Market metrics

MariaDB is the default database in the LAMP stack supplied by Red Hat and SUSE Linux,...
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Licensing and pricing models

MariaDB plc subscriptions cover our free, open source database, Community Server,...
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