DBMS > Hawkular Metrics vs. Manticore Search vs. Microsoft Azure Data Explorer vs. OpenSearch

System Properties Comparison Hawkular Metrics vs. Manticore Search vs. Microsoft Azure Data Explorer vs. OpenSearch

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Editorial information provided by DB-Engines

Name

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.

Fully managed big data interactive analytics platform

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Primary database model

column oriented

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Vector DBMS

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	16.03
Rank	#37	Overall
	#4	Search engines

Website

www.hawkular.org

manticoresearch.com

azure.microsoft.com/services/data-explorer

github.com/opensearch-project
opensearch.org

Technical documentation

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

manual.manticoresearch.com

docs.microsoft.com/en-us/azure/data-explorer

opensearch.org/docs/latest

Developer

Community supported by Red Hat

Manticore Software

Microsoft

Amazon Web Services

Initial release

2014

2017

2019

2021

Current release

6.0, February 2023

cloud service with continuous releases

2.5.0, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL version 2

commercial

Open Source

Apache Version 2.0

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.

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Implementation language

Java

C++

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

hosted

All OS with a Java VM

Data scheme

schema-free

Fixed schema

Fixed schema with schema-less datatypes (dynamic)

schema-free

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

Typing

predefined data types such as float or date

yes

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

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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

all fields are automatically indexed

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL-like query language

Kusto Query Language (KQL), SQL subset

SQL-like query language

APIs and other access methods

HTTP REST

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

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

Java API
RESTful HTTP/JSON API

Supported programming languages

Go
Java
Python
Ruby

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

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Server-side scripts

Stored procedures

user defined functions

Yes, possible languages: KQL, Python, R

yes

Triggers

yes

via Hawkular Alerting

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

by using the 'percolation' feature

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

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Synchronous replication based on Galera library

yes

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Eventual Consistency

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

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

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.

User concepts

Access control

Azure Active Directory Authentication

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
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Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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