DBMS > AlaSQL vs. Apache IoTDB vs. Kyligence Enterprise vs. OpenTSDB vs. VoltDB

System Properties Comparison AlaSQL vs. Apache IoTDB vs. Kyligence Enterprise vs. OpenTSDB vs. VoltDB

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 Time Series DBMS based on HBase

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store
Relational 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	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

alasql.org

iotdb.apache.org

kyligence.io/kyligence-enterprise

opentsdb.net

www.voltdb.com

Technical documentation

github.com/AlaSQL/alasql

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

opentsdb.net/docs/build/html/index.html

docs.voltdb.com

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Kyligence, Inc.

currently maintained by Yahoo and other contributors

VoltDB Inc.

Initial release

2014

2018

2016

2011

2010

Current release

1.1.0, April 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2.0

commercial

Open Source

LGPL

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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, C++

Server operating systems

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

All OS with a Java VM (>= 1.8)

Linux

Linux
Windows

Linux
OS X

for development

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

ANSI SQL for queries (using Apache Calcite)

yes

only a subset of SQL 99

APIs and other access methods

JavaScript API

JDBC
Native API

JDBC
ODBC
RESTful HTTP API

HTTP API
Telnet API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

JavaScript

C
C#
C++
Go
Java
Python
Scala

Erlang
Go
Java
Python
R
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding

based on HBase

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

based on HBase

Multi-source replication
Source-replica replication

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

based on HBase

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

Snapshots and command logging

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 and roles with access to stored procedures

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More resources

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