DBMS > Apache Kylin vs. Apache Pinot vs. H2 vs. Riak KV vs. TerminusDB

System Properties Comparison Apache Kylin vs. Apache Pinot vs. H2 vs. Riak KV vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Distributed, fault tolerant key-value store

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Graph DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

Technical documentation

kylin.apache.org/docs

docs.pinot.apache.org

www.h2database.com/html/main.html

www.tiot.jp/riak-docs/riak/kv/latest

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation, originally contributed from eBay Inc

Apache Software Foundation and contributors

Thomas Mueller

OpenSource, formerly Basho Technologies

DataChemist Ltd.

Initial release

2015

2005

2009

2018

Current release

3.1.0, July 2020

1.0.0, September 2023

2.2.220, July 2023

3.2.0, December 2022

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPL V3

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

Erlang

Prolog, Rust

Server operating systems

Linux

All OS with a Java JDK11 or higher

All OS with a Java VM

Linux
OS X

Linux

Data scheme

yes

schema-free

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

restricted

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

SQL-like query language

yes

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC

JDBC
ODBC

HTTP API
Native Erlang Interface

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

Go
Java
Python

Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

JavaScript
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

no "single point of failure"

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

selectable replication factor

Journaling Streams

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

links between data sets can be stored

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

yes, using Riak Security

Role-based access control

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More resources

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