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DBMS > Atos Standard Common Repository vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. Vitess

System Properties Comparison Atos Standard Common Repository vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. Vitess

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonHazelcast  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonVitess  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 networksA widely adopted in-memory data gridWell established RDBMSFully managed big data interactive analytics platformScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument store
Key-value store
Key-value storeRelational DBMSRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document 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
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryhazelcast.comwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­data-explorervitess.io
Technical documentationhazelcast.org/­imdg/­docsdocs.actian.com/­ingresdocs.microsoft.com/­en-us/­azure/­data-explorervitess.io/­docs
DeveloperAtos Convergence CreatorsHazelcastActian CorporationMicrosoftThe Linux Foundation, PlanetScale
Initial release201620081974 infooriginally developed at University Berkely in early 1970s20192013
Current release17035.3.6, November 202311.2, May 2022cloud service with continuous releases15.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaCGo
Server operating systemsLinuxAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedDocker
Linux
macOS
Data schemeSchema and schema-less with LDAP viewsschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateoptionalyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.yesyes infothe object must implement a serialization strategyno infobut tools for importing/exporting data from/to XML-files availableyes
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like query languageyesKusto Query Language (KQL), SQL subsetyes infowith proprietary extensions
APIs and other access methodsLDAPJCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesAll languages with LDAP bindings.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor ServicesyesYes, possible languages: KQL, Python, Ryes infoproprietary syntax
Triggersyesyes infoEventsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoReplicated MapIngres Replicatoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsone or two-phase-commit; repeatable reads; read commitedACIDnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnonoyes
User concepts infoAccess controlLDAP bind authenticationRole-based access controlfine grained access rights according to SQL-standardAzure Active Directory AuthenticationUsers with fine-grained authorization concept infono user groups or roles

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More resources
Atos Standard Common RepositoryHazelcastIngresMicrosoft Azure Data ExplorerVitess
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