DBMS > H2GIS vs. Hyprcubd vs. NSDb vs. SwayDB

System Properties Comparison H2GIS vs. Hyprcubd vs. NSDb vs. SwayDB

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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.

Description

Spatial extension of H2

Serverless Time Series DBMS

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Spatial DBMS

Time Series DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	0.05
Rank	#372	Overall
	#7	Spatial DBMS

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	0.04
Rank	#373	Overall
	#57	Key-value stores

Website

www.h2gis.org

hyprcubd.com (offline)

nsdb.io

swaydb.simer.au

Technical documentation

www.h2gis.org/docs/home

nsdb.io/Architecture

Developer

CNRS

Hyprcubd, Inc.

Simer Plaha

Initial release

2013

2017

2018

License

Commercial or Open Source

Open Source

LGPL 3.0

commercial

Open Source

Apache Version 2.0

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, Scala

Scala

Server operating systems

hosted

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

yes

SQL-like query language

APIs and other access methods

gRPC (https)

gRPC
HTTP REST
WebSocket

Supported programming languages

Java

Java
Scala

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

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

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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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