DBMS > AlaSQL vs. Apache IoTDB vs. JanusGraph vs. Microsoft Azure Cosmos DB vs. SiteWhere

System Properties Comparison AlaSQL vs. Apache IoTDB vs. JanusGraph vs. Microsoft Azure Cosmos DB vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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 Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Globally distributed, horizontally scalable, multi-model database service

M2M integration platform for persisting/querying time series data

Primary database model

Document store
Relational DBMS

Time Series DBMS

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

alasql.org

iotdb.apache.org

janusgraph.org

azure.microsoft.com/services/cosmos-db

github.com/sitewhere/sitewhere

Technical documentation

github.com/AlaSQL/alasql

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

docs.janusgraph.org

learn.microsoft.com/azure/cosmos-db

sitewhere1.sitewhere.io/index.html

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

SiteWhere

Initial release

2014

2018

2017

2014

2010

Current release

1.1.0, April 2023

0.6.3, February 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

Common Public Attribution License Version 1.0

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

JavaScript

Java

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

All OS with a Java VM (>= 1.8)

Linux
OS X
Unix
Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

predefined scheme

Typing

predefined data types such as float or date

yes

JSON types

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.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL-like query language

APIs and other access methods

JavaScript API

JDBC
Native API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP REST

Supported programming languages

JavaScript

C
C#
C++
Go
Java
Python
Scala

Clojure
Java
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

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

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

yes

Implicit feature of the cloud service

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

via Faunus, a graph analytics engine

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency
Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

Access rights can be defined down to the item level

Users with fine-grained authorization concept

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