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DBMS > Atos Standard Common Repository vs. Datastax Enterprise vs. Microsoft Azure Data Explorer vs. NSDb vs. SWC-DB

System Properties Comparison Atos Standard Common Repository vs. Datastax Enterprise vs. Microsoft Azure Data Explorer vs. NSDb vs. SWC-DB

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNSDb  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.Fully managed big data interactive analytics platformScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA high performance, scalable Wide Column DBMS
Primary database modelDocument store
Key-value store
Wide column storeRelational DBMS infocolumn orientedTime Series DBMSWide column store
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Document store infoIf 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 infothis 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 infosupport 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 infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.93
Rank#56  Overall
#4  Wide column stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.datastax.com/­products/­datastax-enterpriseazure.microsoft.com/­services/­data-explorernsdb.iogithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.datastax.comdocs.microsoft.com/­en-us/­azure/­data-explorernsdb.io/­Architecture
DeveloperAtos Convergence CreatorsDataStaxMicrosoftAlex Kashirin
Initial release20162011201920172020
Current release17036.8, April 2020cloud service with continuous releases0.5, April 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageJavaJavaJava, ScalaC++
Server operating systemsLinuxLinux
OS X
hostedLinux
macOS
Linux
Data schemeSchema and schema-less with LDAP viewsschema-freeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateoptionalyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes: int, bigint, decimal, string
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnoyesnono
Secondary indexesyesyesall fields are automatically indexedall fields are automatically indexed
SQL infoSupport of SQLnoSQL-like DML and DDL statements (CQL); Spark SQLKusto Query Language (KQL), SQL subsetSQL-like query languageSQL-like query language
APIs and other access methodsLDAPProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
gRPC
HTTP REST
WebSocket
Proprietary protocol
Thrift
Supported programming languagesAll languages with LDAP bindingsC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Scala
C++
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Rnono
Triggersyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionSharding infono "single point of failure"Sharding infoImplicit feature of the cloud serviceShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesconfigurable replication factor, datacenter aware, advanced replication for edge computingyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Eventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsno infoAtomicity and isolation are supported for single operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlLDAP bind authenticationAccess rights for users can be defined per objectAzure Active Directory Authentication
More information provided by the system vendor
Atos Standard Common RepositoryDatastax EnterpriseMicrosoft Azure Data ExplorerNSDbSWC-DB infoSuper Wide Column Database
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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More resources
Atos Standard Common RepositoryDatastax EnterpriseMicrosoft Azure Data ExplorerNSDbSWC-DB infoSuper Wide Column Database
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