DBMS > AlaSQL vs. Amazon DynamoDB vs. BigObject vs. jBASE vs. Vitess

System Properties Comparison AlaSQL vs. Amazon DynamoDB vs. BigObject vs. jBASE vs. Vitess

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Analytic DBMS for real-time computations and queries

A robust multi-value DBMS comprising development tools and middleware

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Multivalue DBMS

Relational DBMS

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	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

alasql.org

aws.amazon.com/dynamodb

bigobject.io

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

vitess.io

Technical documentation

github.com/AlaSQL/alasql

docs.aws.amazon.com/dynamodb

docs.bigobject.io

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

vitess.io/docs

Developer

Andrey Gershun & Mathias R. Wulff

Amazon

BigObject, Inc.

Rocket Software (formerly Zumasys)

The Linux Foundation, PlanetScale

Initial release

2014

2012

2015

1991

2013

Current release

5.7

15.0.2, December 2022

License

Commercial or Open Source

Open Source

MIT-License

commercial

free tier for a limited amount of database operations

commercial

free community edition available

commercial

Open Source

Apache Version 2.0, commercial licenses 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.

Implementation language

JavaScript

Server operating systems

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

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

AIX
Linux
Windows

Docker
Linux
macOS

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

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 DML and DDL statements

Embedded SQL for jBASE in BASIC

yes

with proprietary extensions

APIs and other access methods

JavaScript API

RESTful HTTP API

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

JavaScript

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
Basic
Jabbascript
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

Lua

yes

proprietary syntax

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

can be specified for read operations

none

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

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

ACID across one or more tables within a single AWS account and region

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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 and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

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