DBMS > Hawkular Metrics vs. Manticore Search vs. MarkLogic vs. RDF4J vs. Yanza

System Properties Comparison Hawkular Metrics vs. Manticore Search vs. MarkLogic vs. RDF4J vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

Operational and transactional Enterprise NoSQL database

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Time Series DBMS for IoT Applications

Primary database model

Time Series DBMS

Search engine

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

RDF store

Time Series DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.04
Rank	#374	Overall
	#38	Time Series DBMS

Score	0.23
Rank	#317	Overall
	#21	Search engines

Score	6.50
Rank	#56	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#5	Search engines

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

yanza.com

Technical documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

manual.manticoresearch.com

docs.marklogic.com

rdf4j.org/documentation

Developer

Community supported by Red Hat

Manticore Software

MarkLogic Corp.

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Yanza

Initial release

2014

2017

2001

2004

2015

Current release

6.0, February 2023

11.0, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL version 2

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Windows

Data scheme

schema-free

Fixed schema

schema-free

Schema can be enforced

yes

RDF Schemas

schema-free

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

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

SQL92

APIs and other access methods

HTTP REST

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

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API

Supported programming languages

Go
Java
Python
Ruby

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

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Java
PHP
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

yes

via XQuery or JavaScript

yes

Triggers

yes

via Hawkular Alerting

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Synchronous replication based on Galera library

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

can act as a resource manager in an XA/JTA transaction

ACID

Isolation support depends on the API used

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 storage is supported as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, with Range Indexes

User concepts

Access control

Role-based access control at the document and subdocument levels

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