DBMS > Dragonfly vs. Hypertable vs. RavenDB vs. RocksDB vs. Splunk

System Properties Comparison Dragonfly vs. Hypertable vs. RavenDB vs. RocksDB vs. Splunk

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Analytics Platform for Big Data

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

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

Score	2.84
Rank	#101	Overall
	#18	Document stores

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

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

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

ravendb.net

rocksdb.org

www.splunk.com

Technical documentation

www.dragonflydb.io/docs

ravendb.net/docs

github.com/facebook/rocksdb/wiki

docs.splunk.com/Documentation/Splunk

Developer

DragonflyDB team and community contributors

Hypertable Inc.

Hibernating Rhinos

Facebook, Inc.

Splunk Inc.

Initial release

2023

2009

2010

2013

2003

Current release

1.0, March 2023

0.9.8.11, March 2016

5.4, July 2022

9.2.1, May 2024

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

GNU version 3. Commercial license available

Open Source

AGPL version 3, commercial license available

Open Source

BSD

commercial

Limited free edition and free developer edition available

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++

Server operating systems

Linux

Linux
OS X
Windows

an inofficial Windows port is available

Linux
macOS
Raspberry Pi
Windows

Linux

Linux
OS X
Solaris
Windows

Data scheme

scheme-free

schema-free

yes

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

Secondary indexes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like query language (RQL)

Splunk Search Processing Language for search commands

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

C++ API
Thrift

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

C++ API
Java API

HTTP REST

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++
Java
Perl
PHP
Python
Ruby

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

Lua

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor on file system level

Multi-source replication

yes

Multi-source 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

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID, Cluster-wide transaction available

yes

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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

Authorization levels configured per client per database

Access rights for users and roles

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