DBMS > Manticore Search vs. Microsoft Azure Data Explorer vs. MonetDB vs. MySQL vs. Qdrant

System Properties Comparison Manticore Search vs. Microsoft Azure Data Explorer vs. MonetDB vs. MySQL vs. Qdrant

Editorial information provided by DB-Engines

Name

Description

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

Fully managed big data interactive analytics platform

A relational database management system that stores data in columns

Widely used open source RDBMS

A high-performance vector database with neural network or semantic-based matching

Primary database model

Search engine

Relational DBMS

column oriented

Relational DBMS

Key/Value like access via memcached API

Vector DBMS

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

Document store
Spatial DBMS

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

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.28
Rank	#167	Overall
	#7	Vector DBMS

Website

manticoresearch.com

azure.microsoft.com/services/data-explorer

www.monetdb.org

www.mysql.com

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

manual.manticoresearch.com

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

www.monetdb.org/Documentation

dev.mysql.com/doc

qdrant.tech/documentation

Developer

Manticore Software

Microsoft

MonetDB BV

Oracle

since 2010, originally MySQL AB, then Sun

Qdrant

Initial release

2017

2019

2004

1995

2021

Current release

6.0, February 2023

cloud service with continuous releases

Dec2023 (11.49), December 2023

8.4.0, April 2024

License

Commercial or Open Source

Open Source

GPL version 2

commercial

Open Source

Mozilla Public License 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

C++

C and C++

Rust

Server operating systems

FreeBSD
Linux
macOS
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Docker
Linux
macOS
Windows

Data scheme

Fixed schema

Fixed schema with schema-less datatypes (dynamic)

yes

schema-free

Typing

predefined data types such as float or date

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

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

SQL-like query language

Kusto Query Language (KQL), SQL subset

yes

SQL 2003 with some extensions

yes

with proprietary extensions

APIs and other access methods

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

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

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

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

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

Yes, possible languages: KQL, Python, R

yes, in SQL, C, R

yes

proprietary syntax

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

Implicit feature of the cloud service

Sharding via remote tables

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

yes

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

none

Source-replica replication available in experimental status

Multi-source replication
Source-replica replication

Collection-level replication

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
Immediate Consistency

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

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

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Key-based authentication

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