DBMS > Altibase vs. Badger vs. DataFS vs. NSDb

System Properties Comparison Altibase vs. Badger vs. DataFS vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Secondary database models

Graph DBMS

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

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

Score	0.09
Rank	#360	Overall
	#18	Object oriented DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

altibase.com

github.com/dgraph-io/badger

newdatabase.com

nsdb.io

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

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

dev.mobiland.com/Overview.xsp

nsdb.io/Architecture

Developer

Altibase

DGraph Labs

Mobiland AG

Initial release

1999

2017

2018

2017

Current release

v7.3, 2023, August 2023

1.1.263, October 2022

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

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, Scala

Server operating systems

AIX
HP-UX
Linux

BSD
Linux
OS X
Solaris
Windows

Windows

Linux
macOS

Data scheme

yes

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

ANSI SQL-92

SQL-like query language

APIs and other access methods

JDBC
ODBC
Proprietary protocol

.NET Client API
Proprietary client DLL
WinRT client

gRPC
HTTP REST
WebSocket

Supported programming languages

C
C++
Java

.Net
C
C#
C++
VB.Net

Java
Scala

Server-side scripts

Stored procedures

stored procedures and stored functions

Triggers

yes

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Proprietary Sharding system

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

Windows-Profile

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