DBMS > Amazon CloudSearch vs. Axibase vs. Oracle vs. Solr vs. Tibero

System Properties Comparison Amazon CloudSearch vs. Axibase vs. Oracle vs. Solr vs. Tibero

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Widely used RDBMS

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

A secure RDBMS, designed for easy portability from Oracle

Primary database model

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	1.81
Rank	#137	Overall
	#12	Search engines

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

aws.amazon.com/cloudsearch

axibase.com/docs/atsd/finance

www.oracle.com/database

solr.apache.org

us.tmaxsoft.com/products/tibero

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.oracle.com/en/database

solr.apache.org/resources.html

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Amazon

Axibase Corporation

Oracle

Apache Software Foundation

TmaxSoft

Initial release

2012

2013

1980

2006

2003

Current release

15585

23c, September 2023

9.6.1, May 2024

6, April 2015

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

restricted free version is available

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

Java

C and Assembler

Server operating systems

hosted

Linux

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

All OS with a Java VM

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

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

Schemaless in JSON and XML columns

yes

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

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

supports customizable data types and automatic typing

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

all search fields are automatically indexed

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

Solr Parallel SQL Interface

yes

APIs and other access methods

HTTP API

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

Go
Java
PHP
Python
R
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

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

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

Java plugins

Persistent Stored Procedure (PSM)

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

Sharding, horizontal partitioning

Sharding

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

Source-replica replication

Multi-source replication
Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Immediate 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

optimistic locking

ACID

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

planned for next version

User concepts

Access control

authentication via encrypted signatures

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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