DBMS > Citus vs. Ehcache vs. Oracle vs. Sphinx vs. Trino

System Properties Comparison Citus vs. Ehcache vs. Oracle vs. Sphinx vs. Trino

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A widely adopted Java cache with tiered storage options

Widely used RDBMS

Open source search engine for searching in data from different sources, e.g. relational databases

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Secondary database models

Document store

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

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	2.13
Rank	#117	Overall
	#56	Relational DBMS

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Score	5.28
Rank	#61	Overall
	#35	Relational DBMS

Website

www.citusdata.com

www.ehcache.org

www.oracle.com/database

sphinxsearch.com

trino.io

Technical documentation

docs.citusdata.com

www.ehcache.org/documentation

docs.oracle.com/en/database

sphinxsearch.com/docs

trino.io/broadcast
trino.io/docs/current

Developer

Terracotta Inc, owned by Software AG

Oracle

Sphinx Technologies Inc.

Trino Software Foundation

Initial release

2010

2009

1980

2001

2012

2020 rebranded from PrestoSQL

Current release

8.1, December 2018

3.10.0, March 2022

23c, September 2023

3.5.1, February 2023

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is available

Open Source

GPL version 2, commercial licence available

Open Source

Apache Version 2.0

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++

C++

Java

Server operating systems

Linux

All OS with a Java VM

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

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
macOS

for devlopment

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

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.

yes

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

full-text index on all search fields

depending on connected data-source

SQL

Support of SQL

yes

standard, with numerous extensions

yes

with proprietary extensions

SQL-like query language (SphinxQL)

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JCache

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Proprietary protocol

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java

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++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

PL/SQL

also stored procedures in Java possible

yes, depending on connected data-source

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding, horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

yes

by using Terracotta Server

Multi-source replication
Source-replica replication

none

depending on connected data-source

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

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

ACID

isolation level can be parameterized

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

The original contents of fields are not stored in the Sphinx index.

depending on connected data-source

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

fine grained access rights according to SQL-standard

SQL standard access control

More information provided by the system vendor

News

23 is a go, keeping pace with Java
17 September 2024

65: Performance boosts
12 September 2024

64: Control with Open Policy Agent OPA
22 August 2024

63: Querying with JS
1 August 2024

62: A lakehouse that simply works at Prezi
11 July 2024

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