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DBMS > Atos Standard Common Repository vs. CrateDB vs. Hazelcast vs. Microsoft Azure AI Search

System Properties Comparison Atos Standard Common Repository vs. CrateDB vs. Hazelcast vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonCrateDB  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure AI Search  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 networksDistributed Database based on LuceneA widely adopted in-memory data gridSearch-as-a-service for web and mobile app development
Primary database modelDocument store
Key-value store
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeSearch engine
Secondary database modelsRelational DBMSDocument store infoJSON support with IMDG 3.12Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#10  Vector DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score5.52
Rank#59  Overall
#6  Search engines
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycratedb.comhazelcast.comazure.microsoft.com/­en-us/­services/­search
Technical documentationcratedb.com/­docshazelcast.org/­imdg/­docslearn.microsoft.com/­en-us/­azure/­search
DeveloperAtos Convergence CreatorsCrateHazelcastMicrosoft
Initial release2016201320082015
Current release17035.3.6, November 2023V1
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava
Server operating systemsLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VMhosted
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateoptionalyesyesyes
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.yesnoyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like query languageno
APIs and other access methodsLDAPADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindings.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresnouser defined functions (Javascript)yes infoEvent Listeners, Executor Servicesno
Triggersyesnoyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesConfigurable replication on table/partition-levelyes infoReplicated Mapyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Read-after-write consistency on record level
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsno infounique row identifiers can be used for implementing an optimistic concurrency control strategyone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlLDAP bind authenticationrights management via user accountsRole-based access controlyes infousing Azure authentication

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More resources
Atos Standard Common RepositoryCrateDBHazelcastMicrosoft Azure AI Search
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