DBMS > Apache IoTDB vs. LevelDB vs. OrigoDB vs. Transwarp ArgoDB

System Properties Comparison Apache IoTDB vs. LevelDB vs. OrigoDB vs. Transwarp ArgoDB

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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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A fully ACID in-memory object graph database

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Time Series DBMS

Key-value store

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Search engine

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Website

iotdb.apache.org

github.com/google/leveldb

origodb.com

www.transwarp.cn/en/product/argodb

Technical documentation

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

github.com/google/leveldb/blob/main/doc/index.md

origodb.com/docs

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

Apache Software Foundation

Google

Robert Friberg et al

Transwarp

Initial release

2018

2011

2009

under the name LiveDB

Current release

1.1.0, April 2023

1.23, February 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM (>= 1.8)

Illumos
Linux
OS X
Windows

Linux
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

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

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

.NET Client API
HTTP API
LINQ

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

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

none

horizontal partitioning

client side managed; servers are not synchronized

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

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

Foreign keys

Referential integrity

depending on model

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

with automatic compression on writes

yes

Write ahead log

yes

In-memory capabilities

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

yes

User concepts

Access control

yes

Role based authorization

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