DBMS > EsgynDB vs. HarperDB vs. PouchDB vs. RDF4J vs. Splunk

System Properties Comparison EsgynDB vs. HarperDB vs. PouchDB vs. RDF4J vs. Splunk

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

JavaScript DBMS with an API inspired by CouchDB

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

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

Technical documentation

docs.harperdb.io/docs

pouchdb.com/guides

rdf4j.org/documentation

docs.splunk.com/Documentation/Splunk

Developer

Esgyn

HarperDB

Apache Software Foundation

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

Splunk Inc.

Initial release

2015

2017

2012

2004

2003

Current release

3.1, August 2021

7.1.1, June 2019

License

Commercial or Open Source

commercial

free community edition 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

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Java

Node.js

JavaScript

Java

Server operating systems

Linux

Linux
OS X

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Unix
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

dynamic schema

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

via views

yes

SQL

Support of SQL

yes

SQL-like data manipulation statements

Splunk Search Processing Language for search commands

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

HTTP REST

only for PouchDB Server
JavaScript API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

JavaScript

Java
PHP
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

Custom Functions

since release 3.1

View functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

A table resides as a whole on one (or more) nodes in a cluster

Sharding

with a proxy-based framework, named couchdb-lounge

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

the nodes on which a table resides can be defined

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

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

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

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

Durability

Support for making data persistent

yes

yes, using LMDB

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

fine grained access rights according to SQL-standard

Access rights for users and roles

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

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