DBMS > DataFS vs. Elasticsearch vs. Manticore Search vs. SAP HANA

System Properties Comparison DataFS vs. Elasticsearch vs. Manticore Search vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Object oriented DBMS

Search engine

Relational DBMS

Secondary database models

Graph DBMS

Document store
Spatial DBMS
Vector DBMS

Time Series DBMS

using the Manticore Columnar Library

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

newdatabase.com

www.elastic.co/elasticsearch

manticoresearch.com

www.sap.com/products/hana.html

Technical documentation

dev.mobiland.com/Overview.xsp

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

manual.manticoresearch.com

help.sap.com/hana

Developer

Mobiland AG

Elastic

Manticore Software

SAP

Initial release

2018

2010

2017

2010

Current release

1.1.263, October 2022

8.6, January 2023

6.0, February 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Elastic License

Open Source

GPL version 2

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

Windows

All OS with a Java VM

FreeBSD
Linux
macOS
Windows

Appliance or cloud-service

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

Flexible type definitions. Once a type is defined, it is persistent

Fixed schema

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.

Can index from XML

Secondary indexes

yes

All search fields are automatically indexed

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

Java API
RESTful HTTP/JSON API

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

JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
VB.Net

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

user defined functions

SQLScript, R

Triggers

no, except callback-events from server when changes happened

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication based on Galera library

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

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

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.

Memcached and Redis integration

yes

User concepts

Access control

Windows-Profile

yes

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