DBMS > AlaSQL vs. Google Cloud Datastore vs. JaguarDB vs. Lovefield vs. searchxml

System Properties Comparison AlaSQL vs. Google Cloud Datastore vs. JaguarDB vs. Lovefield vs. searchxml

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Performant, highly scalable DBMS for AI and IoT applications

Embeddable relational database for web apps written in pure JavaScript

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Document store
Relational DBMS

Document store

Key-value store
Vector DBMS

Relational DBMS

Native XML DBMS
Search engine

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	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

alasql.org

cloud.google.com/datastore

www.jaguardb.com

google.github.io/lovefield

www.searchxml.net/category/products

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/datastore/docs

www.jaguardb.com/support.html

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

www.searchxml.net/support/handouts

Developer

Andrey Gershun & Mathias R. Wulff

Google

DataJaguar, Inc.

Google

informationpartners gmbh

Initial release

2014

2008

2015

2014

2015

Current release

3.3 July 2023

2.1.12, February 2017

1.0

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

GPL V3.0

Open Source

Apache 2.0

commercial

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

C++

the server part. Clients available in other languages

JavaScript

C++

Server operating systems

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

hosted

Linux

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

tested with Chrome, Firefox, IE, Safari

Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes, details here

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.

yes

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 (GQL)

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JavaScript API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

JDBC
ODBC

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

JavaScript

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

using Google App Engine

yes

on the application server

Triggers

yes

Callbacks using the Google Apps Engine

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication using Paxos

Multi-source replication

none

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

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

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

rights management via user accounts

Domain, group and role-based access control at the document level and for application services

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