DBMS > AlaSQL vs. Faircom DB vs. HugeGraph vs. Memcached vs. Stardog

System Properties Comparison AlaSQL vs. Faircom DB vs. HugeGraph vs. Memcached vs. Stardog

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

A fast-speed and highly-scalable Graph DBMS

In-memory key-value store, originally intended for caching

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Document store
Relational DBMS

Key-value store
Relational DBMS

Graph DBMS

Key-value store

Graph DBMS
RDF store

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

alasql.org

www.faircom.com/products/faircom-db

github.com/hugegraph
hugegraph.apache.org

www.memcached.org

www.stardog.com

Technical documentation

github.com/AlaSQL/alasql

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

hugegraph.apache.org/docs

github.com/memcached/memcached/wiki

docs.stardog.com

Developer

Andrey Gershun & Mathias R. Wulff

FairCom Corporation

Baidu

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Stardog-Union

Initial release

2014

1979

2018

2003

2010

Current release

V12, November 2020

0.9

1.6.25, March 2024

7.3.0, May 2020

License

Commercial or Open Source

Open Source

MIT-License

commercial

Restricted, free version available

Open Source

Apache Version 2.0

Open Source

BSD license

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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++

Java

Server operating systems

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

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

easily portable to other OSs

Linux
macOS
Unix

FreeBSD
Linux
OS X
Unix
Windows

Linux
macOS
Windows

Data scheme

schema-free

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

yes

schema-free

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

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.

Import/export of XML data possible

Secondary indexes

yes

also supports composite index and range index

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

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

yes, ANSI SQL with proprietary extensions

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JavaScript API

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

Java API
RESTful HTTP API
TinkerPop Gremlin

Proprietary protocol

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

JavaScript

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

Groovy
Java
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

asynchronous Gremlin script jobs

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Repcached, a Memcached patch, provides this functionallity

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

Eventual Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

edges in graph

yes

relationships in graphs

Transaction concepts

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

yes

only for local storage and DOM-storage

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

User concepts

Access control

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

Users, roles and permissions

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights for users and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Redis extends the lead in the DB-Engines key-value store ranking
3 February 2014, Matthias Gelbmann

New DB-Engines Ranking shows the popularity of database management systems
3 October 2012, Matthias Gelbmann, Paul Andlinger

show all

Recent citations in the news

Create a Marvel Database with SQL and Javascript, the easy way
2 July 2019, Towards Data Science

HarperDB - How and Why We Built It From The Ground Up on NodeJS
28 February 2021, hackernoon.com

Multi faceted data exploration in the browser using Leaflet and amCharts
3 May 2020, Towards Data Science

provided by Google News

FairCom kicks off new era of database technology USA - English
10 November 2020, PR Newswire

provided by Google News

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

provided by Google News

Why DDoS Threat Actors Are Shifting Their Tactics
15 March 2024, Infosecurity Magazine

Redis Labs Boldly Joins AWS in Dropping Prices From 10 to 40 Percent
27 March 2024, Yahoo Lifestyle UK

Why Redis beats Memcached for caching
14 September 2017, InfoWorld

Introducing mcrouter: A memcached protocol router for scaling memcached deployments
15 September 2014, Facebook Engineering

Memcached DDoS: The biggest, baddest denial of service attacker yet
1 March 2018, ZDNet

provided by Google News

Share this page