DBMS > Hypertable vs. MySQL vs. RavenDB vs. RDF4J vs. Splunk

System Properties Comparison Hypertable vs. MySQL vs. RavenDB vs. RDF4J 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

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

Widely used open source RDBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Analytics Platform for Big Data

Primary database model

Wide column store

Relational DBMS

Key/Value like access via memcached API

Document store

RDF store

Search engine

Secondary database models

Document store
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

Technical documentation

dev.mysql.com/doc

ravendb.net/docs

rdf4j.org/documentation

docs.splunk.com/Documentation/Splunk

Developer

Hypertable Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Hibernating Rhinos

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Splunk Inc.

Initial release

2009

1995

2010

2004

2003

Current release

0.9.8.11, March 2016

8.4.0, April 2024

5.4, July 2022

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

AGPL version 3, commercial license available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Limited free edition and free developer edition available

Cloud-based only

Only available as a cloud service

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Implementation language

C++

C and C++

Java

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Raspberry Pi
Windows

Linux
OS X
Unix
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

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

yes

with proprietary extensions

SQL-like query language (RQL)

Splunk Search Processing Language for search commands

APIs and other access methods

C++ API
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP REST

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Java
PHP
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

Multi-source replication
Source-replica replication

Multi-source replication

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID, Cluster-wide transaction available

ACID

Isolation support depends on the API used

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

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

Users with fine-grained authorization concept

no user groups or roles

Authorization levels configured per client per database

Access rights for users and roles

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