DBMS > Atos Standard Common Repository vs. Manticore Search vs. Microsoft Azure Data Explorer vs. OpenQM vs. Riak KV

System Properties Comparison Atos Standard Common Repository vs. Manticore Search vs. Microsoft Azure Data Explorer vs. OpenQM vs. Riak KV

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

Fully managed big data interactive analytics platform

QpenQM is a high-performance, self-tuning, multi-value DBMS

Distributed, fault tolerant key-value store

Primary database model

Document store
Key-value store

column oriented

with links between data sets and object tags for the creation of secondary indexes

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

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

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

manticoresearch.com

azure.microsoft.com/services/data-explorer

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

manual.manticoresearch.com

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

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Atos Convergence Creators

Manticore Software

Microsoft

Rocket Software, originally Martin Phillips

OpenSource, formerly Basho Technologies

Initial release

2016

2017

2019

1993

2009

Current release

1703

6.0, February 2023

cloud service with continuous releases

3.4-12

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

GPL version 2

commercial

Open Source

GPLv2, extended commercial license available

Open Source

Apache version 2, commercial enterprise edition

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.

Implementation language

Java

C++

Erlang

Server operating systems

Linux

FreeBSD
Linux
macOS
Windows

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
OS X

Data scheme

Schema and schema-less with LDAP views

Fixed schema

Fixed schema with schema-less datatypes (dynamic)

yes

with some exceptions

schema-free

Typing

predefined data types such as float or date

optional

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

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.

yes

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

all fields are automatically indexed

yes

restricted

SQL

Support of SQL

SQL-like query language

Kusto Query Language (KQL), SQL subset

APIs and other access methods

LDAP

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

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

HTTP API
Native Erlang Interface

Supported programming languages

All languages with LDAP bindings

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

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

.Net
Basic
C
Java
Objective C
PHP
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions

Yes, possible languages: KQL, Python, R

yes

Erlang

Triggers

yes

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

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

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

Sharding

Implicit feature of the cloud service

yes

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication based on Galera library

yes

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

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

Atomic execution of specific operations

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.

yes

User concepts

Access control

LDAP bind authentication

Azure Active Directory Authentication

Access rights can be defined down to the item level

yes, using Riak Security

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