DBMS > AlaSQL vs. Dragonfly vs. Faircom DB vs. Oracle NoSQL

System Properties Comparison AlaSQL vs. Dragonfly vs. Faircom DB vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Document store
Relational DBMS

Key-value store

Key-value store
Relational DBMS

Document store
Key-value store
Relational 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	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Website

alasql.org

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.faircom.com/products/faircom-db

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

github.com/AlaSQL/alasql

www.dragonflydb.io/docs

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Andrey Gershun & Mathias R. Wulff

DragonflyDB team and community contributors

FairCom Corporation

Oracle

Initial release

2014

2023

1979

2011

Current release

1.0, March 2023

V12, November 2020

24.1, May 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

BSL 1.1

commercial

Restricted, free version available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

C++

ANSI C, C++

Java

Server operating systems

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

Linux

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux
Solaris SPARC/x86

Data scheme

schema-free

scheme-free

schema free, schema optional, schema required, partial schema,

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

yes, ANSI SQL Types, JSON, typed binary structures

optional

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.

Secondary indexes

yes

SQL

Support of SQL

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

yes, ANSI SQL with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

JavaScript API

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

RESTful HTTP API

Supported programming languages

JavaScript

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

yes

.Net, JavaScript, C/C++

Triggers

yes

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

Atomic execution of command blocks and scripts

tunable from ACID to Eventually Consistent

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

Yes, tunable from durable to delayed durability to in-memory

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

User concepts

Access control

Password-based authentication

Fine grained access rights according to SQL-standard with additional protections for files

Access rights for users and roles

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