DBMS > AlaSQL vs. Google Cloud Spanner vs. IBM Cloudant vs. InfinityDB vs. MySQL

System Properties Comparison AlaSQL vs. Google Cloud Spanner vs. IBM Cloudant vs. InfinityDB vs. MySQL

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Database as a Service offering based on Apache CouchDB

A Java embedded Key-Value Store which extends the Java Map interface

Widely used open source RDBMS

Primary database model

Document store
Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
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	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

alasql.org

cloud.google.com/spanner

www.ibm.com/products/cloudant

boilerbay.com

www.mysql.com

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/spanner/docs

cloud.ibm.com/docs/Cloudant

boilerbay.com/infinitydb/manual

dev.mysql.com/doc

Developer

Andrey Gershun & Mathias R. Wulff

Google

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Boiler Bay Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2014

2017

2010

2002

1995

Current release

4.0

8.4.0, April 2024

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

Erlang

Java

C and C++

Server operating systems

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

hosted

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

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

yes

Query statements complying to ANSI 2011

yes

with proprietary extensions

APIs and other access methods

JavaScript API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

RESTful HTTP/JSON API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

JavaScript

Go
Java
JavaScript (Node.js)
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

Java

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

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication with 3 replicas for regional instances.

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

manual creation possible, using inversions based on multi-value capability

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

Strict serializable isolation

atomic operations within a document possible

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

table locks or row locks depending on storage engine

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

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

Access rights for users can be defined per database

Users with fine-grained authorization concept

no user groups or roles

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