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DBMS > Amazon CloudSearch vs. Hawkular Metrics vs. IBM Db2 warehouse vs. Vertica

System Properties Comparison Amazon CloudSearch vs. Hawkular Metrics vs. IBM Db2 warehouse vs. Vertica

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Cloud-based data warehousing serviceCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelSearch engineTime Series DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#137  Overall
#12  Search engines
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteaws.amazon.com/­cloudsearchwww.hawkular.orgwww.ibm.com/­products/­db2/­warehousewww.vertica.com
Technical documentationdocs.aws.amazon.com/­cloudsearchwww.hawkular.org/­hawkular-metrics/­docs/­user-guidevertica.com/­documentation
DeveloperAmazonCommunity supported by Red HatIBMOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2012201420142005
Current release12.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnoyesno infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemshostedLinux
OS X
Windows
hostedLinux
Data schemeyesschema-freeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyesyes
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.nono infoImport/export of XML data possibleno
Secondary indexesyes infoall search fields are automatically indexednoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnonoyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHTTP APIHTTP REST.NET Client API
JDBC
ODBC
OLE DB
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGo
Java
Python
Ruby
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnonoPL/SQL, SQL PLyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infovia Hawkular Alertingyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredSharding infobased on CassandraShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSselectable replication factor infobased on CassandrayesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
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.noyesno
User concepts infoAccess controlauthentication via encrypted signaturesnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Amazon CloudSearchHawkular MetricsIBM Db2 warehouse infoformerly named IBM dashDBVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Amazon CloudSearchHawkular MetricsIBM Db2 warehouse infoformerly named IBM dashDBVertica infoOpenText™ Vertica™
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