DBMS > Apache Druid vs. Oracle vs. RocksDB vs. Solr

System Properties Comparison Apache Druid vs. Oracle vs. RocksDB vs. Solr

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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

Widely used RDBMS

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

Search engine

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

Spatial DBMS

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

Score	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Score	44.28
Rank	#24	Overall
	#3	Search engines

Website

druid.apache.org

www.oracle.com/database

rocksdb.org

solr.apache.org

Technical documentation

druid.apache.org/docs/latest/design

docs.oracle.com/en/database

github.com/facebook/rocksdb/wiki

solr.apache.org/resources.html

Developer

Apache Software Foundation and contributors

Oracle

Facebook, Inc.

Apache Software Foundation

Initial release

2012

1980

2013

2006

Current release

29.0.1, April 2024

23c, September 2023

8.11.4, April 2024

9.5.0, February 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

restricted free version is available

Open Source

BSD

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

C and C++

C++

Java

Server operating systems

Linux
OS X
Unix

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

Linux

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-less columns are supported

yes

Schemaless in JSON and XML columns

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

SQL for querying

yes

with proprietary extensions

Solr Parallel SQL Interface

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

C++ API
Java API

Java API
RESTful HTTP/JSON API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

C
C++
Go
Java
Perl
Python
Ruby

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding, horizontal partitioning

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

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

isolation level can be parameterized

yes

optimistic locking

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'

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

yes

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