DBMS > Dgraph vs. EsgynDB vs. Faircom DB vs. Manticore Search

System Properties Comparison Dgraph vs. EsgynDB vs. Faircom DB vs. Manticore Search

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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.

Multi-storage database for search, including full-text search.

Primary database model

Graph DBMS

Relational DBMS

Key-value store
Relational DBMS

Search engine

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	1.39
Rank	#155	Overall
	#15	Graph DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	0.18
Rank	#314	Overall
	#45	Key-value stores
	#141	Relational DBMS

Score	0.23
Rank	#301	Overall
	#21	Search engines

Website

dgraph.io

www.esgyn.cn

www.faircom.com/products/faircom-db

manticoresearch.com

Technical documentation

dgraph.io/docs

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

manual.manticoresearch.com

Developer

Dgraph Labs, Inc.

Esgyn

FairCom Corporation

Manticore Software

Initial release

2016

2015

1979

2017

Current release

V13, July 2024

6.0, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Restricted, free version available

Open Source

GPL version 2

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++

Server operating systems

Linux
OS X
Windows

Linux

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

easily portable to other OSs

FreeBSD
Linux
macOS
Windows

Data scheme

schema-free

yes

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

Fixed schema

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

yes, ANSI SQL with proprietary extensions

SQL-like query language

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

ADO.NET
JDBC
ODBC

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

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

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

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

.Net, JavaScript, C/C++

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

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).

Synchronous replication based on Galera library

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

The original contents of fields are not stored in the Manticore index.

In-memory capabilities

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

yes

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

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

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More resources

Recent citations in the news

Top Open Source Graph Databases
3 June 2024, MarkTechPost

Dgraph on AWS: Setting up a horizontally scalable graph database
1 September 2020, AWS Blog

Dgraph raises $11.5 million for scalable graph database solutions
31 July 2019, VentureBeat

Graph Database Market size to grow by USD 7.40 billion between 2022 - 2027 | Growth Driven by Lack of standardization and programming flexibility - Technavio
13 December 2023, Yahoo Finance

provided by Google News

FairCom Unveils New Look, FairCom DB v13: Introducing 'DB Made Simple'
4 June 2024, Business Wire

provided by Google News

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2 May 2023, hackernoon.com

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25 July 2022, hackernoon.com

Integrating Manticore Search with Apache Superset
8 August 2023, hackernoon.com

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24 May 2020, hackernoon.com

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27 April 2023, hackernoon.com

provided by Google News

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