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DBMS > Atos Standard Common Repository vs. Derby vs. HBase vs. Manticore Search vs. Microsoft Azure Data Explorer

System Properties Comparison Atos Standard Common Repository vs. Derby vs. HBase vs. Manticore Search vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDerby infooften called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDB  Xexclude from comparisonHBase  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Data Explorer  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 networksFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Wide-column store based on Apache Hadoop and on concepts of BigTableMulti-storage database for search, including full-text search.Fully managed big data interactive analytics platform
Primary database modelDocument store
Key-value store
Relational DBMSWide column storeSearch engineRelational DBMS infocolumn oriented
Secondary database modelsTime Series DBMS infousing the Manticore Columnar LibraryDocument 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.71
Rank#69  Overall
#37  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.22
Rank#312  Overall
#21  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorydb.apache.org/­derbyhbase.apache.orgmanticoresearch.comazure.microsoft.com/­services/­data-explorer
Technical documentationdb.apache.org/­derby/­manuals/­index.htmlhbase.apache.org/­book.htmlmanual.manticoresearch.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAtos Convergence CreatorsApache Software FoundationApache Software Foundation infoApache top-level project, originally developed by PowersetManticore SoftwareMicrosoft
Initial release20161997200820172019
Current release170310.17.1.0, November 20232.3.4, January 20216.0, February 2023cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache version 2Open Source infoGPL version 2commercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaC++
Server operating systemsLinuxAll OS with a Java VMLinux
Unix
Windows infousing Cygwin
FreeBSD
Linux
macOS
Windows
hosted
Data schemeSchema and schema-less with LDAP viewsyesschema-free, schema definition possibleFixed schemaFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateoptionalyesoptions to bring your own types, AVROInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.yesyesnoCan index from XMLyes
Secondary indexesyesyesnoyes infofull-text index on all search fieldsall fields are automatically indexed
SQL infoSupport of SQLnoyesnoSQL-like query languageKusto Query Language (KQL), SQL subset
APIs and other access methodsLDAPJDBCJava API
RESTful HTTP API
Thrift
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindingsJavaC
C#
C++
Groovy
Java
PHP
Python
Scala
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoJava Stored Proceduresyes infoCoprocessors in Javauser defined functionsYes, possible languages: KQL, Python, R
Triggersyesyesyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationMulti-source replication
Source-replica replication
Synchronous replication based on Galera libraryyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDSingle row ACID (across millions of columns)yes infoisolated transactions for atomic changes and binary logging for safe writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlLDAP bind authenticationfine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnoAzure Active Directory Authentication

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More resources
Atos Standard Common RepositoryDerby infooften called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDBHBaseManticore SearchMicrosoft Azure Data Explorer
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