DBMS > EsgynDB vs. Faircom EDGE vs. KeyDB vs. Percona Server for MongoDB vs. TinkerGraph

System Properties Comparison EsgynDB vs. Faircom EDGE vs. KeyDB vs. Percona Server for MongoDB vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Key-value store

Document store

Graph DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

www.esgyn.cn

www.faircom.com/products/faircom-edge

github.com/Snapchat/KeyDB
keydb.dev

www.percona.com/mongodb/software/percona-server-for-mongodb

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

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

docs.keydb.dev

docs.percona.com/percona-distribution-for-mongodb

Developer

Esgyn

FairCom Corporation

EQ Alpha Technology Ltd.

Percona

Initial release

2015

1979

2019

2015

2009

Current release

V3, October 2020

3.4.10-2.10, November 2017

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

BSD-3

Open Source

GPL Version 2

Open Source

Apache 2.0

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

C++, Java

ANSI C, C++

C++

Java

Server operating systems

Linux

Android
Linux

ARM, x86
Raspbian
Windows

Linux

Data scheme

yes

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

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

SQL

Support of SQL

yes

ANSI SQL queries

APIs and other access methods

ADO.NET
JDBC
ODBC

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

Proprietary protocol

RESP - REdis Serialization Protoco

proprietary protocol using JSON

TinkerPop 3

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Groovy
Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

.Net, JavaScript, C/C++

Lua

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

Synchronous and asynchronous realtime replication based on transaction logs

Multi-source replication
Source-replica replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Eventual Consistency
Immediate Consistency

none

Foreign keys

Referential integrity

yes

when using SQL

yes

Relationships in graphs

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

optional

In-memory capabilities

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

yes

via In-Memory Engine

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

simple password-based access control and ACL

Access rights for users and roles

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