DBMS > Ignite vs. Manticore Search vs. MaxDB vs. Oracle

System Properties Comparison Ignite vs. Manticore Search vs. MaxDB vs. Oracle

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Editorial information provided by DB-Engines

Name

Description

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

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

A robust and reliable RDBMS optimized to run all major SAP solutions

Widely used RDBMS

Primary database model

Key-value store
Relational DBMS

Search engine

Relational DBMS

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	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

ignite.apache.org

manticoresearch.com

maxdb.sap.com

www.oracle.com/database

Technical documentation

apacheignite.readme.io/docs

manual.manticoresearch.com

maxdb.sap.com/documentation

docs.oracle.com/en/database

Developer

Apache Software Foundation

Manticore Software

SAP, acquired from Software AG (Adabas-D) in 1997

Oracle

Initial release

2015

2017

1984

1980

Current release

Apache Ignite 2.6

6.0, February 2023

7.9.10.12, February 2024

23c, September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL version 2

commercial

Limited community edition free

commercial

restricted free version is available

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

C++, Java, .Net

C++

C and C++

Server operating systems

Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

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

Data scheme

yes

Fixed schema

yes

Schemaless in JSON and XML columns

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.

yes

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

ADO.NET
JDBC
ODBC
WebDAV

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net
C#
Java
Perl
PHP
Python

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

yes (compute grid and cache interceptors can be used instead)

user defined functions

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Synchronous replication based on Galera library

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

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'

User concepts

Access control

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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