DBMS > Apache IoTDB vs. Datomic vs. MariaDB vs. TempoIQ vs. TimesTen

System Properties Comparison Apache IoTDB vs. Datomic vs. MariaDB vs. TempoIQ vs. TimesTen

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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.

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

In-Memory RDBMS compatible to Oracle

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	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

iotdb.apache.org

www.datomic.com

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

tempoiq.com (offline)

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

docs.datomic.com

mariadb.com/kb/en/library

docs.oracle.com/database/timesten-18.1

Developer

Apache Software Foundation

Cognitect

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

The lead developer Monty Widenius is the original author of MySQL

TempoIQ

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2018

2012

2009

Fork of MySQL, which was first released in 1995

2012

1998

Current release

1.1.0, April 2023

1.0.6735, June 2023

11.3.2, February 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

limited edition free

Open Source

GPL version 2, commercial enterprise subscription available

commercial

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

Java, Clojure

C and C++

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

Dynamic columns are supported

schema-free

yes

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

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
Native API

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Clojure
Java

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

C#
Java
JavaScript

Node.js
Python
Ruby

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

PL/SQL compatibility added with version 10.3

PL/SQL

Triggers

yes

By using transaction functions

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

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

none

But extensive use of caching in the application peers

several options for horizontal partitioning and Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

not for in-memory storage engine

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

recommended only for testing and development

yes

with MEMORY storage engine

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

simple authentication-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

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