DBMS > Datomic vs. Hypertable vs. IRONdb vs. MySQL vs. Splunk

System Properties Comparison Datomic vs. Hypertable vs. IRONdb vs. MySQL 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.

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Widely used open source RDBMS

Analytics Platform for Big Data

Primary database model

Key/Value like access via memcached API

Search engine

Secondary database models

Document store
Spatial DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

www.datomic.com

www.circonus.com/solutions/time-series-database/

www.mysql.com

www.splunk.com

Technical documentation

docs.datomic.com

docs.circonus.com/irondb/category/getting-started

dev.mysql.com/doc

docs.splunk.com/Documentation/Splunk

Developer

Cognitect

Hypertable Inc.

Circonus LLC.

Oracle

since 2010, originally MySQL AB, then Sun

Splunk Inc.

Initial release

2012

2009

2017

1995

2003

Current release

1.0.6735, June 2023

0.9.8.11, March 2016

V0.10.20, January 2018

8.4.0, April 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

GNU version 3. Commercial license available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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

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Implementation language

Java, Clojure

C++

C and C++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

with proprietary extensions

Splunk Search Processing Language for search commands

APIs and other access methods

RESTful HTTP API

C++ API
Thrift

HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST

Supported programming languages

Clojure
Java

C++
Java
Perl
PHP
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

yes, in Lua

yes

proprietary syntax

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

Automatic, metric affinity per node

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

selectable replication factor on file system level

configurable replication factor, datacenter aware

Multi-source replication
Source-replica replication

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

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

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

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

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