DBMS > EsgynDB vs. Faircom DB vs. IRONdb vs. Memgraph

System Properties Comparison EsgynDB vs. Faircom DB vs. IRONdb vs. Memgraph

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

An open source graph database built for real-time streaming and compatible with Neo4j

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Graph DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

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

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

Website

www.esgyn.cn

www.faircom.com/products/faircom-db

www.circonus.com/solutions/time-series-database/

memgraph.com

Technical documentation

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

docs.circonus.com/irondb/category/getting-started

memgraph.com/docs

Social network pages

Developer

Esgyn

FairCom Corporation

Circonus LLC.

Memgraph Ltd

Initial release

2015

1979

2017

Current release

V12, November 2020

V0.10.20, January 2018

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

BSL 1.1; commercial license for enterprise edition 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

C++, Java

ANSI C, C++

C and C++

Server operating systems

Linux

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

easily portable to other OSs

Linux

Data scheme

yes

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

schema-free

schema-free and schema-optional

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

yes

text, numeric, histograms

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.

Secondary indexes

yes

SQL

Support of SQL

yes

yes, ANSI SQL with proprietary extensions

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

ADO.NET
JDBC
ODBC

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

HTTP API

Bolt protocol
Cypher query language

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

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

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

yes

.Net, JavaScript, C/C++

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Automatic, metric affinity per node

Sharding

dynamic graph partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

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

configurable replication factor, datacenter aware

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

ACID

with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

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

yes

with periodic snapshot and write-ahead logging (WAL) of changes

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

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

Users, roles and permissions

More information provided by the system vendor

Specific characteristics

Memgraph directly connects to your streaming infrastructure so you and your team...
» more

Competitive advantages

Business Source License ensures a future for the Memgraph community MAGE algorithm...
» more

Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
» more

Licensing and pricing models

You can check out our pricing model and licenses on the company website .
» more

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