DBMS > Manticore Search vs. Microsoft Azure Data Explorer vs. Microsoft SQL Server vs. TerminusDB

System Properties Comparison Manticore Search vs. Microsoft Azure Data Explorer vs. Microsoft SQL Server vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

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

Fully managed big data interactive analytics platform

Microsofts flagship relational DBMS

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

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

Document store
Graph DBMS
Spatial DBMS

Document store
RDF store

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

Score	0.23
Rank	#301	Overall
	#21	Search engines

Score	3.28
Rank	#83	Overall
	#45	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Website

manticoresearch.com

azure.microsoft.com/services/data-explorer

www.microsoft.com/en-us/sql-server

terminusdb.com

Technical documentation

manual.manticoresearch.com

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

learn.microsoft.com/en-US/sql/sql-server

terminusdb.github.io/terminusdb/#

Developer

Manticore Software

Microsoft

DataChemist Ltd.

Initial release

2017

2019

1989

2018

Current release

6.0, February 2023

cloud service with continuous releases

SQL Server 2022, November 2022

11.0.0, January 2023

License

Commercial or Open Source

Open Source

GPL version 2

commercial

restricted free version is available

Open Source

GPL V3

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++

Prolog, Rust

Server operating systems

FreeBSD
Linux
macOS
Windows

hosted

Linux
Windows

Linux

Data scheme

Fixed schema

Fixed schema with schema-less datatypes (dynamic)

yes

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

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

SQL

Support of SQL

SQL-like query language

Kusto Query Language (KQL), SQL subset

yes

SQL-like query language (WOQL)

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

Yes, possible languages: KQL, Python, R

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

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

tables can be distributed across several files (horizontal partitioning); sharding through federation

Graph Partitioning

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.

yes, but depending on the SQL-Server Edition

Journaling Streams

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

Foreign keys

Referential integrity

yes

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

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 journaling

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

Role-based access control

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