DBMS > Apache Druid vs. Heroic vs. Kinetica vs. Microsoft Azure Table Storage vs. Oracle

System Properties Comparison Apache Druid vs. Heroic vs. Kinetica vs. Microsoft Azure Table Storage vs. Oracle

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Fully vectorized database across both GPUs and CPUs

A Wide Column Store for rapid development using massive semi-structured datasets

Widely used RDBMS

Primary database model

Relational DBMS
Time Series DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	3.55
Rank	#80	Overall
	#6	Wide column stores

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Website

druid.apache.org

github.com/spotify/heroic

www.kinetica.com

azure.microsoft.com/en-us/services/storage/tables

www.oracle.com/database

Technical documentation

druid.apache.org/docs/latest/design

spotify.github.io/heroic

docs.kinetica.com

docs.oracle.com/en/database

Developer

Apache Software Foundation and contributors

Spotify

Kinetica

Microsoft

Oracle

Initial release

2012

2014

2012

1980

Current release

30.0.0, June 2024

7.1, August 2021

23c, September 2023

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++

C and C++

Server operating systems

Linux
OS X
Unix

Linux

hosted

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

Data scheme

yes

schema-less columns are supported

schema-free

yes

schema-free

yes

Schemaless in JSON and XML columns

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

via Elasticsearch

yes

SQL

Support of SQL

SQL for querying

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

JDBC
RESTful HTTP/JSON API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C++
Java
JavaScript (Node.js)
Python

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
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

user defined functions

PL/SQL

also stored procedures in Java possible

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

Source-replica replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

optimistic locking

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

GPU vRAM or System RAM

yes

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

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users and roles on table level

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

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