DBMS > AlaSQL vs. Apache IoTDB vs. atoti vs. FatDB

System Properties Comparison AlaSQL vs. Apache IoTDB vs. atoti vs. FatDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

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

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Primary database model

Document store
Relational DBMS

Time Series DBMS

Object oriented DBMS

Document store
Key-value store

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	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Website

alasql.org

iotdb.apache.org

atoti.io

Technical documentation

github.com/AlaSQL/alasql

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

docs.atoti.io

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

ActiveViam

FatCloud

Initial release

2014

2018

2012

Current release

1.1.0, April 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2.0

commercial

free versions available

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

JavaScript

Java

Server operating systems

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

All OS with a Java VM (>= 1.8)

Windows

Data scheme

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

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

SQL-like query language

Multidimensional Expressions (MDX)

Via inetgration in SQL Server

APIs and other access methods

JavaScript API

JDBC
Native API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Supported programming languages

JavaScript

C
C#
C++
Go
Java
Python
Scala

Server-side scripts

Stored procedures

yes

Python

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding, horizontal partitioning

Sharding

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

selectable replication factor

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

none

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

Can implement custom security layer via applications

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