DBMS > Badger vs. Hyprcubd vs. MySQL vs. RavenDB vs. Riak KV

System Properties Comparison Badger vs. Hyprcubd vs. MySQL vs. RavenDB vs. Riak KV

Editorial information provided by DB-Engines

Name

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.

Serverless Time Series DBMS

Widely used open source RDBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

Distributed, fault tolerant key-value store

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Document store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Document store
Spatial DBMS

Graph DBMS
Spatial DBMS
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	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

github.com/dgraph-io/badger

hyprcubd.com (offline)

www.mysql.com

ravendb.net

Technical documentation

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

dev.mysql.com/doc

ravendb.net/docs

www.tiot.jp/riak-docs/riak/kv/latest

Developer

DGraph Labs

Hyprcubd, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Hibernating Rhinos

OpenSource, formerly Basho Technologies

Initial release

2017

1995

2010

2009

Current release

8.4.0, April 2024

5.4, July 2022

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

AGPL version 3, commercial license available

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

Erlang

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Raspberry Pi
Windows

Linux
OS X

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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.

yes

Secondary indexes

yes

restricted

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

SQL-like query language (RQL)

APIs and other access methods

gRPC (https)

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Multi-source 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

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

links between data sets can be stored

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

token access

Users with fine-grained authorization concept

no user groups or roles

Authorization levels configured per client per database

yes, using Riak Security

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