DBMS > Badger vs. Ehcache vs. Microsoft SQL Server vs. PouchDB vs. STSdb

System Properties Comparison Badger vs. Ehcache vs. Microsoft SQL Server vs. PouchDB vs. STSdb

Editorial information provided by DB-Engines

Name

Description

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

A widely adopted Java cache with tiered storage options

Microsofts flagship relational DBMS

JavaScript DBMS with an API inspired by CouchDB

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

github.com/dgraph-io/badger

www.ehcache.org

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

pouchdb.com

github.com/STSSoft/STSdb4

Technical documentation

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

www.ehcache.org/documentation

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

pouchdb.com/guides

Developer

DGraph Labs

Terracotta Inc, owned by Software AG

Microsoft

Apache Software Foundation

STS Soft SC

Initial release

2017

2009

1989

2012

2011

Current release

3.10.0, March 2022

SQL Server 2022, November 2022

7.1.1, June 2019

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is available

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

JavaScript

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

via views

SQL

Support of SQL

yes

APIs and other access methods

JCache

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

HTTP REST

only for PouchDB Server
JavaScript API

.NET Client API

Supported programming languages

Java

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

JavaScript

C#
Java

Server-side scripts

Stored procedures

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

View functions in JavaScript

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

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

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by using Terracotta Server

yes, but depending on the SQL-Server Edition

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

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