DBMS > Apache IoTDB vs. RDF4J vs. SingleStore vs. Splunk

System Properties Comparison Apache IoTDB vs. RDF4J vs. SingleStore vs. Splunk

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Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Analytics Platform for Big Data

Primary database model

Secondary database models

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	4.02
Rank	#74	Overall
	#39	Relational DBMS

Score	93.02
Rank	#13	Overall
	#2	Search engines

Website

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

rdf4j.org/documentation

docs.singlestore.com

docs.splunk.com/Documentation/Splunk

Developer

Apache Software Foundation

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

SingleStore Inc.

Splunk Inc.

Initial release

2018

2004

2013

2003

Current release

1.1.0, April 2023

8.5, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

free developer edition 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

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

Implementation language

Java

C++, Go

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Unix
Windows

Linux

64 bit version required

Linux
OS X
Solaris
Windows

Data scheme

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

yes

SQL

Support of SQL

SQL-like query language

yes

but no triggers and foreign keys

Splunk Search Processing Language for search commands

APIs and other access methods

JDBC
Native API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

HTTP REST

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java
PHP
Python

Bash
C
C#
Java
JavaScript (Node.js)
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

none

Sharding

hash partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

none

Source-replica replication

stores two copies of each physical data partition on two separate nodes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

can define user-defined aggregate functions for map-reduce-style calculations

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

yes

Fine grained access control via users, groups and roles

Access rights for users and roles

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More resources

DB-Engines blog posts

Turbocharge Your Application Development Using WebAssembly With SingleStoreDB
17 October 2022, Akmal Chaudhri, SingleStore (sponsor)

Cloud-Based Analytics With SingleStoreDB
9 June 2022, Akmal Chaudhri, SingleStore (sponsor)

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022, Akmal Chaudhri, SingleStore (sponsor)

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2 July 2014, Paul Andlinger

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