DBMS > Badger vs. Dragonfly vs. FatDB vs. Hyprcubd

System Properties Comparison Badger vs. Dragonfly vs. FatDB vs. Hyprcubd

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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.

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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

Serverless Time Series DBMS

Primary database model

Key-value store

Document store
Key-value store

Time Series DBMS

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

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

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Website

github.com/dgraph-io/badger

github.com/dragonflydb/dragonfly
www.dragonflydb.io

hyprcubd.com (offline)

Technical documentation

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

www.dragonflydb.io/docs

Developer

DGraph Labs

DragonflyDB team and community contributors

FatCloud

Hyprcubd, Inc.

Initial release

2017

2023

2012

Current release

1.0, March 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSL 1.1

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Windows

hosted

Data scheme

schema-free

scheme-free

schema-free

yes

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

yes

time, int, uint, float, 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

SQL

Support of SQL

Via inetgration in SQL Server

SQL-like query language

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

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

gRPC (https)

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

Server-side scripts

Stored procedures

Lua

yes

via applications

Triggers

publish/subscribe channels provide some trigger functionality

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of command blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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

Password-based authentication

Can implement custom security layer via applications

token access

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More resources

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provided by Google News

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