DBMS > AlaSQL vs. Apache IoTDB vs. Kyligence Enterprise vs. NSDb

System Properties Comparison AlaSQL vs. Apache IoTDB vs. Kyligence Enterprise vs. NSDb

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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 distributed analytics engine for big data, built on top of Apache Kylin

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Time Series DBMS

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

Score	0.49
Rank	#259	Overall
	#40	Document stores
	#120	Relational DBMS

Score	1.19
Rank	#176	Overall
	#15	Time Series DBMS

Score	0.39
Rank	#276	Overall
	#125	Relational DBMS

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Website

alasql.org

iotdb.apache.org

kyligence.io/kyligence-enterprise

nsdb.io

Technical documentation

github.com/AlaSQL/alasql

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

nsdb.io/Architecture

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Kyligence, Inc.

Initial release

2014

2018

2016

2017

Current release

1.1.0, April 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

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

Java, Scala

Server operating systems

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

All OS with a Java VM (>= 1.8)

Linux

Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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 fields are automatically indexed

SQL

Support of SQL

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

SQL-like query language

ANSI SQL for queries (using Apache Calcite)

SQL-like query language

APIs and other access methods

JavaScript API

JDBC
Native API

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
WebSocket

Supported programming languages

JavaScript

C
C#
C++
Go
Java
Python
Scala

Java
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

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

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

Immediate Consistency

Eventual 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

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

Using Apache Lucene

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

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