DBMS > Apache Pinot vs. EventStoreDB vs. KairosDB vs. RDF4J vs. SAP HANA

System Properties Comparison Apache Pinot vs. EventStoreDB vs. KairosDB vs. RDF4J vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Distributed Time Series DBMS based on Cassandra or H2

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

pinot.apache.org

www.eventstore.com

github.com/kairosdb/kairosdb

rdf4j.org

www.sap.com/products/hana.html

Technical documentation

docs.pinot.apache.org

developers.eventstore.com

kairosdb.github.io

rdf4j.org/documentation

help.sap.com/hana

Developer

Apache Software Foundation and contributors

Event Store Limited

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

SAP

Initial release

2015

2012

2013

2004

2010

Current release

1.0.0, September 2023

21.2, February 2021

1.2.2, November 2018

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

All OS with a Java JDK11 or higher

Linux
Windows

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Appliance or cloud-service

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC

Graphite protocol
HTTP REST
Telnet API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC

Supported programming languages

Go
Java
Python

Java
JavaScript

Node.js
PHP
Python

Java
PHP
Python

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on Cassandra

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

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

simple password-based access control

yes

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