DBMS > AlaSQL vs. Apache Druid vs. H2 vs. SQream DB

System Properties Comparison AlaSQL vs. Apache Druid vs. H2 vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Document store
Relational DBMS

Relational 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	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	0.73
Rank	#228	Overall
	#105	Relational DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

druid.apache.org/docs/latest/design

www.h2database.com/html/main.html

docs.sqream.com

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation and contributors

Thomas Mueller

SQream Technologies

Initial release

2014

2012

2005

2017

Current release

29.0.1, April 2024

2.2.220, July 2023

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache license v2

Open Source

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

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

C++, CUDA, Haskell, Java, Scala

Server operating systems

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

Linux
OS X
Unix

All OS with a Java VM

Linux

Data scheme

schema-free

yes

schema-less columns are supported

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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 for querying

yes

APIs and other access methods

JavaScript API

JDBC
RESTful HTTP/JSON API

JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

JavaScript

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

none

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, via HDFS, S3 or other storage engines

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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, 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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

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