DBMS > AlaSQL vs. Apache IoTDB vs. SQream DB vs. STSdb

System Properties Comparison AlaSQL vs. Apache IoTDB vs. SQream DB vs. STSdb

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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 GPU-based, columnar RDBMS for big data analytics workloads

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

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	0.70
Rank	#227	Overall
	#104	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

alasql.org

iotdb.apache.org

sqream.com

github.com/STSSoft/STSdb4

Technical documentation

github.com/AlaSQL/alasql

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

docs.sqream.com

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

SQream Technologies

STS Soft SC

Initial release

2014

2018

2017

2011

Current release

1.1.0, April 2023

2022.1.6, December 2022

4.0.8, September 2015

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2.0

commercial

Open Source

GPLv2, commercial license available

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

C++, CUDA, Haskell, Java, Scala

Server operating systems

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

All OS with a Java VM (>= 1.8)

Linux

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

yes

primitive types and user defined types (classes)

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

yes

APIs and other access methods

JavaScript API

JDBC
Native API

.Net
JDBC
ODBC

.NET Client API

Supported programming languages

JavaScript

C
C#
C++
Go
Java
Python
Scala

C++
Java
JavaScript (Node.js)
Python

C#
Java

Server-side scripts

Stored procedures

yes

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

horizontal and vertical partitioning

none

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

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

none

Eventual Consistency
Strong Consistency with Raft

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

ACID

Concurrency

Support for concurrent manipulation of data

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

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