DBMS > Badger vs. EJDB vs. FatDB vs. Microsoft SQL Server vs. Oracle NoSQL

System Properties Comparison Badger vs. EJDB vs. FatDB vs. Microsoft SQL Server vs. Oracle NoSQL

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

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)

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Microsofts flagship relational DBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Key-value store

Document store

Document store
Key-value store

Relational DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

github.com/dgraph-io/badger

github.com/Softmotions/ejdb

www.microsoft.com/en-us/sql-server

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

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

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

learn.microsoft.com/en-US/sql/sql-server

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

DGraph Labs

Softmotions

FatCloud

Microsoft

Oracle

Initial release

2017

2012

1989

2011

Current release

SQL Server 2022, November 2022

23.3, December 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2

commercial

restricted free version is available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

Server operating systems

BSD
Linux
OS X
Solaris
Windows

server-less

Windows

Linux
Windows

Linux
Solaris SPARC/x86

Data scheme

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

optional

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

SQL

Support of SQL

Via inetgration in SQL Server

yes

SQL-like DML and DDL statements

APIs and other access methods

in-process shared library

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

RESTful HTTP API

Supported programming languages

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

via applications

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes, but depending on the SQL-Server Edition

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

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

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

off heap cache

User concepts

Access control

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

Access rights for users and roles

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