DBMS > Badger vs. H2GIS vs. Hyprcubd vs. Yanza

System Properties Comparison Badger vs. H2GIS vs. Hyprcubd vs. Yanza

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Editorial information provided by DB-Engines

Name

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

Yanza 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.

Spatial extension of H2

Serverless Time Series DBMS

Time Series DBMS for IoT Applications

Primary database model

Key-value store

Spatial DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

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

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

github.com/dgraph-io/badger

www.h2gis.org

hyprcubd.com (offline)

yanza.com

Technical documentation

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

www.h2gis.org/docs/home

Developer

DGraph Labs

CNRS

Hyprcubd, Inc.

Yanza

Initial release

2017

2013

2015

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

LGPL 3.0

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

SQL-like query language

APIs and other access methods

gRPC (https)

HTTP API

Supported programming languages

Java

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

based on H2

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

based on H2

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Immediate 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

yes, multi-version concurrency control (MVCC)

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

yes

based on H2

token access

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