DBMS > Apache IoTDB vs. ArcadeDB vs. Snowflake vs. TinkerGraph

System Properties Comparison Apache IoTDB vs. ArcadeDB vs. Snowflake vs. TinkerGraph

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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

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Cloud-based data warehousing service for structured and semi-structured data

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Time Series DBMS

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

Graph DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

iotdb.apache.org

arcadedb.com

www.snowflake.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

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

docs.arcadedb.com

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Arcade Data

Snowflake Computing Inc.

Initial release

2018

2021

2014

2009

Current release

1.1.0, April 2023

September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

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

SQL-like query language, no joins

yes

APIs and other access methods

JDBC
Native API

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

CLI Client
JDBC
ODBC

TinkerPop 3

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java

JavaScript (Node.js)
Python

Groovy
Java

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

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

yes

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

yes

none

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

none

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Relationships in graphs

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

optional

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

Users with fine-grained authorization concept, user roles and pluggable authentication

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