DBMS > Hyprcubd vs. Manticore Search vs. NSDb vs. RDF4J

System Properties Comparison Hyprcubd vs. Manticore Search vs. NSDb vs. RDF4J

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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

Serverless Time Series DBMS

Multi-storage database for search, including full-text search.

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

hyprcubd.com (offline)

manticoresearch.com

nsdb.io

rdf4j.org

Technical documentation

manual.manticoresearch.com

nsdb.io/Architecture

rdf4j.org/documentation

Developer

Hyprcubd, Inc.

Manticore Software

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2017

2004

Current release

6.0, February 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

Apache Version 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java, Scala

Java

Server operating systems

hosted

FreeBSD
Linux
macOS
Windows

Linux
macOS

Linux
OS X
Unix
Windows

Data scheme

yes

Fixed schema

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

yes: int, bigint, decimal, 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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

gRPC (https)

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

gRPC
HTTP REST
WebSocket

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Java
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

Using Apache Lucene

yes

in-memory storage is supported as well

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

token access

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