DBMS > AlaSQL vs. Google BigQuery vs. Lovefield vs. Machbase Neo vs. SQLite

System Properties Comparison AlaSQL vs. Google BigQuery vs. Lovefield vs. Machbase Neo vs. SQLite

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Large scale data warehouse service with append-only tables

Embeddable relational database for web apps written in pure JavaScript

TimeSeries DBMS for AIoT and BigData

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

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	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

alasql.org

cloud.google.com/bigquery

google.github.io/lovefield

machbase.com

www.sqlite.org

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/bigquery/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

machbase.com/dbms

www.sqlite.org/docs.html

Developer

Andrey Gershun & Mathias R. Wulff

Google

Machbase

Dwayne Richard Hipp

Initial release

2014

2010

2014

2013

2000

Current release

2.1.12, February 2017

V8.0, August 2023

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache 2.0

commercial

free test version available

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

Server operating systems

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

hosted

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

tested with Chrome, Firefox, IE, Safari

Linux
macOS
Windows

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

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

yes

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

JavaScript API

RESTful HTTP/JSON API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

JavaScript

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

Triggers

yes

Using read-only observers

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

selectable replication factor

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

Since BigQuery is designed for querying data

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

volatile and lookup table

yes

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

simple password-based access control

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