DBMS > AlaSQL vs. Altibase vs. Google Cloud Firestore vs. MySQL vs. Sqrrl

System Properties Comparison AlaSQL vs. Altibase vs. Google Cloud Firestore vs. MySQL vs. Sqrrl

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

JavaScript DBMS library

An enterprise grade, high-performance RDBMS

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Widely used open source RDBMS

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store

Relational DBMS

Key/Value like access via memcached API

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store
Spatial 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	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

alasql.org

altibase.com

firebase.google.com/products/firestore

www.mysql.com

sqrrl.com

Technical documentation

github.com/AlaSQL/alasql

github.com/ALTIBASE/Documents/tree/master/Manuals

firebase.google.com/docs/firestore

dev.mysql.com/doc

Developer

Andrey Gershun & Mathias R. Wulff

Altibase

Google

Oracle

since 2010, originally MySQL AB, then Sun

Amazon

originally Sqrrl Data, Inc.

Initial release

2014

1999

2017

1995

2012

Current release

v7.3, 2023, August 2023

8.4.0, April 2024

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open source edition discontinued with March 2023

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

JavaScript

C++

C and C++

Java

Server operating systems

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

AIX
HP-UX
Linux

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

ANSI SQL-92

yes

with proprietary extensions

APIs and other access methods

JavaScript API

JDBC
ODBC
Proprietary protocol

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

JavaScript

C
C++
Java

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

stored procedures and stored functions

yes, Firebase Rules & Cloud Functions

yes

proprietary syntax

Triggers

yes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication

Multi-source replication
Source-replica replication

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

yes

ACID

not for MyISAM storage engine

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Users with fine-grained authorization concept

no user groups or roles

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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