DBMS > Badger vs. EJDB vs. Faircom DB vs. Sequoiadb

System Properties Comparison Badger vs. EJDB vs. Faircom DB vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

NewSQL database with distributed OLTP and SQL

Primary database model

Key-value store

Document store

Key-value store
Relational DBMS

Document store
Relational DBMS

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

Score	0.12
Rank	#306	Overall
	#46	Key-value stores

Score	0.10
Rank	#314	Overall
	#41	Document stores

Score	0.34
Rank	#266	Overall
	#40	Key-value stores
	#122	Relational DBMS

Score	0.42
Rank	#256	Overall
	#39	Document stores
	#120	Relational DBMS

Website

github.com/dgraph-io/badger

ejdb.org

www.faircom.com/products/faircom-db

www.sequoiadb.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

github.com/Softmotions/ejdb/blob/master/README.md

learn.faircomcorp.com/developers/documentation_directory

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

DGraph Labs

Softmotions

FairCom Corporation

Sequoiadb Ltd.

Initial release

2017

2012

1979

2013

Current release

V12, November 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2

commercial

Restricted, free version available

Open Source

Server: AGPL; Client: Apache V2

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

ANSI C, C++

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

server-less

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

easily portable to other OSs

Linux

Data scheme

schema-free

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

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes, ANSI SQL Types, JSON, typed binary structures

yes

oid, date, timestamp, binary, regex

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, ANSI SQL with proprietary extensions

SQL-like query language

APIs and other access methods

in-process shared library

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

proprietary protocol using JSON

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

JavaScript

Triggers

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

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

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

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

User concepts

Access control

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

simple password-based access control

More information provided by the system vendor

Specific characteristics

Achieve Hundreds of Thousands of Transactions Per Second on A Single Database Server...
» more

Competitive advantages

Top Features SQL Key-value store and navigational NoSQL API Indexed binary objects...
» more

Typical application scenarios

Real-time transaction processing solutions leverage FairCom DB because its NoSQL...
» more

Key customers

Microsoft, UPS, Verizon, Motorola, Commvault, Thomson Reuters, ACI, BNY Mellon, Rockwell...
» more

Market metrics

From banking and financial transactions, transportation, warehouse automation, package...
» more

Licensing and pricing models

Just as the technical aspects of FairCom DB are flexible to meet operation requirements,...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

Recent citations in the news

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

provided by Google News

SequoiaDB Raises New Round Led By CICC Capital
13 October 2020, China Money Network

Understanding open source databases
18 February 2021, VentureBeat

provided by Google News

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