DBMS > Hyprcubd vs. Oracle Berkeley DB vs. Riak KV vs. TypeDB

System Properties Comparison Hyprcubd vs. Oracle Berkeley DB vs. Riak KV vs. TypeDB

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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

Widely used in-process key-value store

Distributed, fault tolerant key-value store

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

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

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

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

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

hyprcubd.com (offline)

www.oracle.com/database/technologies/related/berkeleydb.html

typedb.com

Technical documentation

docs.oracle.com/cd/E17076_05/html/index.html

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

typedb.com/docs

Developer

Hyprcubd, Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

OpenSource, formerly Basho Technologies

Vaticle

Initial release

1994

2009

2016

Current release

18.1.40, May 2020

3.2.0, December 2022

2.26.3, January 2024

License

Commercial or Open Source

commercial

Open Source

commercial license available

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPL Version 3, commercial licenses available

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, Java, C++ (depending on the Berkeley DB edition)

Erlang

Java

Server operating systems

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

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

only with the Berkeley DB XML edition

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

SQL-like query language

yes

SQL interfaced based on SQLite is available

APIs and other access methods

gRPC (https)

HTTP API
Native Erlang Interface

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

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

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

Erlang

Triggers

yes

only for the SQL API

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

substituted by the relationship feature

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

yes, using Riak Security

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

TypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more

Competitive advantages

TypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more

Typical application scenarios

Life sciences : TypeDB makes working with biological data much easier and accelerates...
» more

Licensing and pricing models

Apache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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