DBMS > Apache IoTDB vs. OrigoDB vs. RavenDB vs. SWC-DB vs. Yanza

System Properties Comparison Apache IoTDB vs. OrigoDB vs. RavenDB vs. SWC-DB vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded 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

A fully ACID in-memory object graph database

Open Source Operational and Transactional Enterprise NoSQL Document Database

A high performance, scalable Wide Column DBMS

Time Series DBMS for IoT Applications

Primary database model

Time Series DBMS

Document store
Object oriented DBMS

Document store

Wide column store

Time Series DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

Time Series 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	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

iotdb.apache.org

origodb.com

ravendb.net

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

yanza.com

Technical documentation

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

origodb.com/docs

ravendb.net/docs

Developer

Apache Software Foundation

Robert Friberg et al

Hibernating Rhinos

Alex Kashirin

Yanza

Initial release

2018

2009

under the name LiveDB

2010

2020

2015

Current release

1.1.0, April 2023

5.4, July 2022

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL version 3, commercial license available

Open Source

GPL V3

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

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

Linux
macOS
Raspberry Pi
Windows

Linux

Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

SQL-like query language (RQL)

SQL-like query language

APIs and other access methods

JDBC
Native API

.NET Client API
HTTP API
LINQ

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Proprietary protocol
Thrift

HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

yes

Timer and event based

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

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

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Authorization levels configured per client per database

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