DBMS > Apache Kylin vs. Apache Pinot vs. Atos Standard Common Repository vs. Hawkular Metrics vs. Oracle

System Properties Comparison Apache Kylin vs. Apache Pinot vs. Atos Standard Common Repository vs. Hawkular Metrics vs. Oracle

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

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

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Widely used RDBMS

Primary database model

Relational DBMS

Document store
Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Website

kylin.apache.org

pinot.apache.org

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.hawkular.org

www.oracle.com/database

Technical documentation

kylin.apache.org/docs

docs.pinot.apache.org

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.oracle.com/en/database

Developer

Apache Software Foundation, originally contributed from eBay Inc

Apache Software Foundation and contributors

Atos Convergence Creators

Community supported by Red Hat

Oracle

Initial release

2015

2016

2014

1980

Current release

3.1.0, July 2020

1.0.0, September 2023

1703

23c, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

commercial

restricted free version is 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 and C++

Server operating systems

Linux

All OS with a Java JDK11 or higher

Linux

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes

optional

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

ANSI SQL for queries (using Apache Calcite)

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC

LDAP

HTTP REST

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Java
Python

All languages with LDAP bindings

Go
Java
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

cell division

Sharding

based on Cassandra

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

Atomic execution of specific operations

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

LDAP bind authentication

fine grained access rights according to SQL-standard

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