DBMS > Dragonfly vs. HBase vs. Raima Database Manager vs. RocksDB

System Properties Comparison Dragonfly vs. HBase vs. Raima Database Manager vs. RocksDB

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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

Wide-column store based on Apache Hadoop and on concepts of BigTable

RDBMS with a small footprint, either embedded into an application or used as a database server

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Key-value store

Wide column store

Relational DBMS
Time Series DBMS

Key-value store

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

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	0.49
Rank	#259	Overall
	#121	Relational DBMS
	#21	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

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

hbase.apache.org

raima.com

rocksdb.org

Technical documentation

www.dragonflydb.io/docs

hbase.apache.org/book.html

docs.raima.com

github.com/facebook/rocksdb/wiki

Developer

DragonflyDB team and community contributors

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Raima Inc.

Facebook, Inc.

Initial release

2023

2008

1984

2013

Current release

1.0, March 2023

2.3.4, January 2021

15, June 2021

9.2.1, May 2024

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache version 2

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C++

Server operating systems

Linux

Linux
Unix
Windows

using Cygwin

Android
HP-UX
Integrity RTOS
iOS
Linux
OS X
QNX
Solaris
VxWorks
Windows

Linux

Data scheme

scheme-free

schema-free, schema definition possible

yes

schema-free

Typing

predefined data types such as float or date

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

options to bring your own types, AVRO

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.

Exporting/Importing of XML structures possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC
RESTful HTTP API

C++ API
Java API

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
C
C++
Objective-C
PL/SQL

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Lua

yes

Coprocessors in Java

yes

based on the ANSI/ISO SQL Persistent Stored Modules (PSM) specification

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

yes

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 or Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

Single row ACID (across millions of columns)

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

yes, multi-version concurrency control (MVCC)

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

More information provided by the system vendor

Specific characteristics

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Competitive advantages

Decreased time-to-market Industry-standard interfaces & tools for making your job...
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Typical application scenarios

Typical use cases include: Internet of Things (IoT) Embedded In-Memory Database Time-Series...
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Key customers

Infor, ABB, The Boeing Company, BAE Systems, Dow Jones, Dun & Bradstreet, Fujitsu,...
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Market metrics

Over 30 000 applications developers worldwide have field-tested RDM products More...
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Licensing and pricing models

Just as the technical aspects of Raima Database Manager are flexible, so are the...
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News

Raima Unveils RaimaDB 16.0: Elevating Database Performance and User Experience
29 February 2024

Raima Announces Release of Raima Database Manager (RDM) v15, a Powerful Embedded Time Series Database
10 June 2021

Raima Announces Release of Raima Database Manager (RDM) v14.2, a Powerful IoT Edge Embedded Database
8 October 2020

Raima Joins BlackBerry QNX Channel Partner Program to Deliver Safety-Critical and Secure Software Solutions
1 October 2020

Raima Expands Their Reseller Network in Asia
19 May 2020

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.