DBMS > AlaSQL vs. Cloudflare Workers KV vs. GBase vs. InfinityDB vs. MySQL

System Properties Comparison AlaSQL vs. Cloudflare Workers KV vs. GBase vs. InfinityDB vs. MySQL

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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	0.39
Rank	#274	Overall
	#39	Key-value stores

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

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

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

alasql.org

www.cloudflare.com/developer-platform/workers-kv

www.gbase.cn

boilerbay.com

www.mysql.com

Technical documentation

github.com/AlaSQL/alasql

developers.cloudflare.com/kv/api

boilerbay.com/infinitydb/manual

dev.mysql.com/doc

Developer

Andrey Gershun & Mathias R. Wulff

Cloudflare

General Data Technology Co., Ltd.

Boiler Bay Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2014

2018

2004

2002

1995

Current release

GBase 8a, GBase 8s, GBase 8c

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

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

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

JavaScript

C, Java, Python

Java

C and C++

Server operating systems

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

hosted

Linux

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

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.

Standard with numerous extensions

yes

with proprietary extensions

APIs and other access methods

JavaScript API

HTTP REST
Proprietary protocol

ADO.NET
C API
JDBC
ODBC

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

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

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

user defined functions

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

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

Optimistic locking for transactions; no isolation for bulk loads

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

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

yes

Users with fine-grained authorization concept

no user groups or roles

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