DBMS > Interbase vs. Manticore Search vs. Microsoft Azure Table Storage vs. Oracle vs. Sphinx

System Properties Comparison Interbase vs. Manticore Search vs. Microsoft Azure Table Storage vs. Oracle vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Light-weight proven RDBMS

originally from Borland

Multi-storage database for search, including full-text search.

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

Widely used RDBMS

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

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

www.embarcadero.com/products/interbase

manticoresearch.com

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

www.oracle.com/database

sphinxsearch.com

Technical documentation

docs.embarcadero.com/products/interbase

manual.manticoresearch.com

docs.oracle.com/en/database

sphinxsearch.com/docs

Developer

Embarcadero

Manticore Software

Microsoft

Oracle

Sphinx Technologies Inc.

Initial release

1984

2017

2012

1980

2001

Current release

InterBase 2020, December 2019

6.0, February 2023

23c, September 2023

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2

commercial

restricted free version is available

Open Source

GPL version 2, commercial licence available

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

C++

C and C++

C++

Server operating systems

Android
iOS
Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

hosted

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

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

Fixed schema

schema-free

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

export as XML data possible

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language

yes

with proprietary extensions

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
JDBC
ODBC

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Proprietary protocol

Supported programming languages

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

user defined functions

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Interbase Change Views

Synchronous replication based on Galera library

yes

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

Multi-source replication
Source-replica replication

none

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

optimistic locking

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

Durability

Support for making data persistent

yes

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

yes

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

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

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

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