DBMS > Couchbase vs. Hyprcubd vs. Manticore Search vs. Realm vs. UniData,UniVerse

System Properties Comparison Couchbase vs. Hyprcubd vs. Manticore Search vs. Realm vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

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

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Serverless Time Series DBMS

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Time Series DBMS

using the Manticore Columnar Library

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

www.couchbase.com

hyprcubd.com (offline)

manticoresearch.com

realm.io

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.couchbase.com

manual.manticoresearch.com

realm.io/docs

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Couchbase, Inc.

Hyprcubd, Inc.

Manticore Software

Realm, acquired by MongoDB in May 2019

Rocket Software

Initial release

2011

2017

2014

1985

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

6.0, February 2023

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Open Source

GPL version 2

Open Source

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, C++, Go and Erlang

C++

Server operating systems

Linux
OS X
Windows

hosted

FreeBSD
Linux
macOS
Windows

Android
Backend: server-less
iOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

Fixed schema

yes

schema-free

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

optional

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

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like query language

yes

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

gRPC (https)

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

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

.Net
Java

with Android only
Objective-C
React Native
Swift

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

user defined functions

runs within the applications so server-side scripts are unnecessary

yes

Triggers

yes

via the TAP protocol

yes

Change Listeners

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Synchronous replication based on Galera library

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

configurable

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.

yes

In-memory capabilities

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

yes

Ephemeral buckets

yes

In-Memory realm

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

token access

yes

Access rights according to SQL-standard and operating system based

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