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DBMS > Amazon CloudSearch vs. Atos Standard Common Repository vs. CrateDB vs. Hawkular Metrics

System Properties Comparison Amazon CloudSearch vs. Atos Standard Common Repository vs. CrateDB vs. Hawkular Metrics

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonCrateDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksDistributed Database based on LuceneHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.
Primary database modelSearch engineDocument store
Key-value store
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#137  Overall
#12  Search engines
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Websiteaws.amazon.com/­cloudsearchatos.net/en/convergence-creators/portfolio/standard-common-repositorycratedb.comwww.hawkular.org
Technical documentationdocs.aws.amazon.com/­cloudsearchcratedb.com/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperAmazonAtos Convergence CreatorsCrateCommunity supported by Red Hat
Initial release2012201620132014
Current release1703
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJavaJava
Server operating systemshostedLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
OS X
Windows
Data schemeyesSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesoptionalyesyes
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.yesnono
Secondary indexesyes infoall search fields are automatically indexedyesyesno
SQL infoSupport of SQLnonoyes, but no triggers and constraints, and PostgreSQL compatibilityno
APIs and other access methodsHTTP APILDAPADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
HTTP REST
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
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresnonouser defined functions (Javascript)no
Triggersnoyesnoyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredSharding infocell divisionShardingSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSyesConfigurable replication on table/partition-levelselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
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
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsno infounique row identifiers can be used for implementing an optimistic concurrency control strategyno
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.yesnono
User concepts infoAccess controlauthentication via encrypted signaturesLDAP bind authenticationrights management via user accountsno
More information provided by the system vendor
Amazon CloudSearchAtos Standard Common RepositoryCrateDBHawkular Metrics
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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More resources
Amazon CloudSearchAtos Standard Common RepositoryCrateDBHawkular Metrics
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