DBMS > Hyprcubd vs. LevelDB vs. Oracle Berkeley DB vs. SiteWhere

System Properties Comparison Hyprcubd vs. LevelDB vs. Oracle Berkeley DB vs. SiteWhere

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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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Widely used in-process key-value store

M2M integration platform for persisting/querying time series data

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

Time Series DBMS

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

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Score	0.07
Rank	#347	Overall
	#33	Time Series DBMS

Website

hyprcubd.com (offline)

github.com/google/leveldb

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

github.com/sitewhere/sitewhere

Technical documentation

github.com/google/leveldb/blob/main/doc/index.md

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

sitewhere1.sitewhere.io/index.html

Developer

Hyprcubd, Inc.

Google

Oracle

originally developed by Sleepycat, which was acquired by Oracle

SiteWhere

Initial release

2011

1994

2010

Current release

1.23, February 2021

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

commercial license available

Open Source

Common Public Attribution License Version 1.0

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

Java

Server operating systems

hosted

Illumos
Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

predefined scheme

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

SQL

Support of SQL

SQL-like query language

yes

SQL interfaced based on SQLite is available

APIs and other access methods

gRPC (https)

HTTP REST

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.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

Server-side scripts

Stored procedures

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

with automatic compression on writes

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

Users with fine-grained authorization concept

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