DBMS > AlaSQL vs. etcd vs. Faircom EDGE vs. OceanBase

System Properties Comparison AlaSQL vs. etcd vs. Faircom EDGE vs. OceanBase

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

A distributed, high available RDBMS compatible with Oracle and MySQL

Primary database model

Document store
Relational DBMS

Key-value store

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Wide column store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.42
Rank	#264	Overall
	#42	Document stores
	#122	Relational DBMS

Score	7.05
Rank	#53	Overall
	#5	Key-value stores

Score	0.02
Rank	#370	Overall
	#55	Key-value stores
	#157	Relational DBMS

Score	1.97
Rank	#119	Overall
	#58	Relational DBMS

Website

alasql.org

etcd.io
github.com/etcd-io/etcd

www.faircom.com/products/faircom-edge

en.oceanbase.com

Technical documentation

github.com/AlaSQL/alasql

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

en.oceanbase.com/docs/oceanbase-database

Developer

Andrey Gershun & Mathias R. Wulff

FairCom Corporation

OceanBase

previously Alibaba and Ant Group

Initial release

2014

1979

2010

Current release

3.4, August 2019

V3, October 2020

4.3.0, April 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2.0

commercial

Restricted, free version available

Open Source

Commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

ANSI C, C++

C++

Server operating systems

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

FreeBSD
Linux
Windows

experimental

Android
Linux

ARM, x86
Raspbian
Windows

Linux

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

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.

yes

ANSI SQL queries

yes

APIs and other access methods

JavaScript API

gRPC
JSON over HTTP

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

Supported programming languages

JavaScript

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

Triggers

yes

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning

Customizable business rules for partitioning

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

Replication methods

Methods for redundantly storing data on multiple nodes

none

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

Synchronous and asynchronous realtime replication based on transaction logs

Multi-source replication using Paxos

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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 user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Access rights for users, groups and roles according to SQL-standard

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