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DBMS > Amazon CloudSearch vs. Datomic vs. Vertica vs. WakandaDB

System Properties Comparison Amazon CloudSearch vs. Datomic vs. Vertica vs. WakandaDB

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonDatomic  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityCloud 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.WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelSearch engineRelational DBMSRelational DBMS infoColumn orientedObject oriented DBMS
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
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteaws.amazon.com/­cloudsearchwww.datomic.comwww.vertica.comwakanda.github.io
Technical documentationdocs.aws.amazon.com/­cloudsearchdocs.datomic.comvertica.com/­documentationwakanda.github.io/­doc
DeveloperAmazonCognitectOpenText infopreviously Micro Focus and Hewlett PackardWakanda SAS
Initial release2012201220052012
Current release1.0.6735, June 202312.0.3, January 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freecommercial infoLimited community edition freeOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++C++, JavaScript
Server operating systemshostedAll OS with a Java VMLinuxLinux
OS X
Windows
Data schemeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.yes
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.nonono
Secondary indexesyes infoall search fields are automatically indexedyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.no
APIs and other access methodsHTTP APIRESTful HTTP APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
RESTful HTTP API
Supported programming languagesClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
JavaScript
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsyes, PostgreSQL PL/pgSQL, with minor differencesyes
TriggersnoBy using transaction functionsyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requirednone infoBut extensive use of caching in the application peershorizontal partitioning, hierarchical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSnone infoBut extensive use of caching in the application peersMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnono
User concepts infoAccess controlauthentication via encrypted signaturesnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashyes
More information provided by the system vendor
Amazon CloudSearchDatomicVertica infoOpenText™ Vertica™WakandaDB
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
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 CloudSearchDatomicVertica infoOpenText™ Vertica™WakandaDB
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