DBMS > Apache IoTDB vs. OrigoDB vs. Quasardb vs. TimesTen

System Properties Comparison Apache IoTDB vs. OrigoDB vs. Quasardb vs. TimesTen

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Editorial information provided by DB-Engines

Name

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

A fully ACID in-memory object graph database

Distributed, high-performance timeseries database

In-Memory RDBMS compatible to Oracle

Primary database model

Time Series DBMS

Document store
Object oriented DBMS

Time Series DBMS

Relational DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

iotdb.apache.org

origodb.com

quasar.ai

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

Technical documentation

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

origodb.com/docs

doc.quasar.ai/master

docs.oracle.com/database/timesten-18.1

Developer

Apache Software Foundation

Robert Friberg et al

quasardb

Oracle, TimesTen Performance Software, HP

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

Initial release

2018

2009

under the name LiveDB

2009

1998

Current release

1.1.0, April 2023

3.14.1, January 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

commercial

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.

Implementation language

Java

C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
Windows

BSD
Linux
OS X
Windows

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

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

yes

integer and binary

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.

can be achieved using .NET

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

.NET Client API
HTTP API
LINQ

HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

PL/SQL

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

client side managed; servers are not synchronized

Sharding

consistent hashing

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

Source-replica replication

Source-replica replication with selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

with Hadoop integration

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

depending on model

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

by using LevelDB

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

Transient mode

yes

User concepts

Access control

yes

Role based authorization

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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