DBMS > Atos Standard Common Repository vs. BaseX vs. Microsoft Azure Data Explorer vs. Newts

System Properties Comparison Atos Standard Common Repository vs. BaseX vs. Microsoft Azure Data Explorer vs. Newts

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	BaseX  Xexclude from comparison	Microsoft Azure Data Explorer  Xexclude from comparison	Newts  Xexclude from comparison
	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	Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.	Fully managed big data interactive analytics platform	Time Series DBMS based on Cassandra
Primary database model	Document store Key-value store	Native XML DBMS	Relational DBMS column oriented	Time Series DBMS
Secondary database models			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 1.84 Rank #135   Overall #4   Native XML DBMS	Score 3.80 Rank #81   Overall #43   Relational DBMS	Score 0.07 Rank #375   Overall #41   Time Series DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	basex.org	azure.microsoft.com/­services/­data-explorer	opennms.github.io/­newts
Technical documentation		docs.basex.org	docs.microsoft.com/­en-us/­azure/­data-explorer	github.com/­OpenNMS/­newts/­wiki
Developer	Atos Convergence Creators	BaseX GmbH	Microsoft	OpenNMS Group
Initial release	2016	2007	2019	2014
Current release	1703	11.0, June 2024	cloud service with continuous releases
License Commercial or Open Source	commercial	Open Source BSD license	commercial	Open Source Apache 2.0
Cloud-based only Only available as a cloud service	no	no	yes	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	Java	Java		Java
Server operating systems	Linux	Linux OS X Windows	hosted	Linux OS X Windows
Data scheme	Schema and schema-less with LDAP views	schema-free	Fixed schema with schema-less datatypes (dynamic)	schema-free
Typing predefined data types such as float or date	optional	no XQuery supports types	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.	yes		yes	no
Secondary indexes	yes	yes	all fields are automatically indexed	no
SQL Support of SQL	no	no	Kusto Query Language (KQL), SQL subset	no
APIs and other access methods	LDAP	Java API RESTful HTTP API RESTXQ WebDAV XML:DB XQJ	Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API	HTTP REST Java API
Supported programming languages	All languages with LDAP bindings	Actionscript C C# Haskell Java JavaScript Node.js Lisp Perl PHP Python Qt Rebol Ruby Scala Visual Basic	.Net Go Java JavaScript (Node.js) PowerShell Python R	Java
Server-side scripts Stored procedures	no	yes	Yes, possible languages: KQL, Python, R	no
Triggers	yes	yes via events	yes see docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy	no
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	none	Sharding Implicit feature of the cloud service	Sharding based on Cassandra
Replication methods Methods for redundantly storing data on multiple nodes	yes	none	yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.	selectable replication factor based on Cassandra
MapReduce Offers an API for user-defined Map/Reduce methods		no	Spark connector (open source): github.com/­Azure/­azure-kusto-spark	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration		Eventual Consistency Immediate Consistency	Eventual Consistency based on Cassandra Immediate Consistency based on Cassandra
Foreign keys Referential integrity	no	no	no	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	multiple readers, single writer	no	no
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	yes	yes	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes		no	no
User concepts Access control	LDAP bind authentication	Users with fine-grained authorization concept on 4 levels	Azure Active Directory Authentication	no
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More resources
	Atos Standard Common Repository	BaseX	Microsoft Azure Data Explorer	Newts
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