DBMS > AlaSQL vs. Google BigQuery vs. Solr vs. SQL.JS vs. SQLite

System Properties Comparison AlaSQL vs. Google BigQuery vs. Solr vs. SQL.JS vs. SQLite

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Large scale data warehouse service with append-only tables

A widely used distributed, scalable search engine based on Apache Lucene

Port of SQLite to JavaScript

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Relational DBMS

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

alasql.org

cloud.google.com/bigquery

solr.apache.org

sql.js.org

www.sqlite.org

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/bigquery/docs

solr.apache.org/resources.html

sql.js.org/documentation/index.html

www.sqlite.org/docs.html

Developer

Andrey Gershun & Mathias R. Wulff

Google

Apache Software Foundation

Alon Zakai

enhancements implemented by others

Dwayne Richard Hipp

Initial release

2014

2010

2006

2012

2000

Current release

9.6.0, April 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache Version 2

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Java

JavaScript

Server operating systems

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

hosted

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

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

server-less

Data scheme

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

dynamic column types

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

yes

not rigid because of 'dynamic typing' concept.

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

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

yes

Solr Parallel SQL Interface

yes

SQL-92 is not fully supported

yes

SQL-92 is not fully supported

APIs and other access methods

JavaScript API

RESTful HTTP/JSON API

Java API
RESTful HTTP/JSON API

JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

JavaScript

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Java plugins

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

none

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

Since BigQuery is designed for querying data

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

except by serializing a db to a file

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

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