DBMS > AlaSQL vs. Apache IoTDB vs. Bangdb vs. Drizzle vs. H2

System Properties Comparison AlaSQL vs. Apache IoTDB vs. Bangdb vs. Drizzle vs. H2

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines 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

Converged and high performance database for device data, events, time series, document and graph

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Primary database model

Document store
Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Spatial 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	0.15
Rank	#334	Overall
	#45	Document stores
	#31	Graph DBMS
	#31	Time Series DBMS

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

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

docs.bangdb.com

www.h2database.com/html/main.html

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Sachin Sinha, BangDB

Drizzle project, originally started by Brian Aker

Thomas Mueller

Initial release

2014

2018

2012

2008

2005

Current release

1.1.0, April 2023

BangDB 2.0, October 2021

7.2.4, September 2012

2.2.220, July 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2.0

Open Source

BSD 3

Open Source

GNU GPL

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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, C++

C++

Java

Server operating systems

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

All OS with a Java VM (>= 1.8)

Linux

FreeBSD
Linux
OS X

All OS with a Java VM

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

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

SQL-like query language

SQL like support with command line tool

yes

with proprietary extensions

yes

APIs and other access methods

JavaScript API

JDBC
Native API

Proprietary protocol
RESTful HTTP API

JDBC

JDBC
ODBC

Supported programming languages

JavaScript

C
C#
C++
Go
Java
Python
Scala

C
C#
C++
Java
Python

C
C++
Java
PHP

Java

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

Triggers

yes

yes, Notifications (with Streaming only)

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

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

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication
Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

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

Tunable consistency, set CAP knob accordingly

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

yes, optimistic concurrency control

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

yes, run db with in-memory only mode

yes

User concepts

Access control

yes

yes (enterprise version only)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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