DBMS > Badger vs. BigObject vs. Blueflood vs. DataFS

System Properties Comparison Badger vs. BigObject vs. Blueflood vs. DataFS

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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.

Analytic DBMS for real-time computations and queries

Scalable TimeSeries DBMS based on Cassandra

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.

Primary database model

Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Object oriented DBMS

Secondary database models

Graph DBMS

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

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Website

github.com/dgraph-io/badger

bigobject.io

blueflood.io

newdatabase.com

Technical documentation

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

docs.bigobject.io

github.com/rax-maas/blueflood/wiki

dev.mobiland.com/Overview.xsp

Developer

DGraph Labs

BigObject, Inc.

Rackspace

Mobiland AG

Initial release

2017

2015

2013

2018

Current release

1.1.263, October 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free community edition available

Open Source

Apache 2.0

commercial

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

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X

Windows

Data scheme

schema-free

yes

predefined scheme

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

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

SQL-like DML and DDL statements

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

HTTP REST

.NET Client API
Proprietary client DLL
WinRT client

Supported programming languages

.Net
C
C#
C++
VB.Net

Server-side scripts

Stored procedures

Lua

Triggers

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Proprietary Sharding system

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

User concepts

Access control

Windows-Profile

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