DBMS > Dragonfly vs. Hawkular Metrics vs. OpenEdge vs. Oracle Berkeley DB vs. Oracle Rdb

System Properties Comparison Dragonfly vs. Hawkular Metrics vs. OpenEdge vs. Oracle Berkeley DB vs. Oracle Rdb

Editorial information provided by DB-Engines

Name

Description

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Application development environment with integrated database management system

Widely used in-process key-value store

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

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

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

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

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.hawkular.org

www.progress.com/openedge

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

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

Technical documentation

www.dragonflydb.io/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

documentation.progress.com/output/ua/OpenEdge_latest

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

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

DragonflyDB team and community contributors

Community supported by Red Hat

Progress Software Corporation

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2023

2014

1984

1994

1984

Current release

1.0, March 2023

OpenEdge 12.2, March 2020

18.1.40, May 2020

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache 2.0

commercial

Open Source

commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

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

Server operating systems

Linux

Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

HP Open VMS

Data scheme

scheme-free

schema-free

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

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

yes

close to SQL 92

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

HTTP REST

JDBC
ODBC

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

Go
Java
Python
Ruby

Progress proprietary ABL (Advanced Business Language)

.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

Lua

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

via Hawkular Alerting

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

since Version 11.4

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

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

Password-based authentication

Users and groups

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