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DBMS > Amazon CloudSearch vs. Spark SQL vs. Vertica vs. WakandaDB

System Properties Comparison Amazon CloudSearch vs. Spark SQL vs. Vertica vs. WakandaDB

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonSpark SQL  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudSpark SQL is a component on top of 'Spark Core' for structured data processingCloud 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
Score1.81
Rank#137  Overall
#12  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Score0.10
Rank#356  Overall
#17  Object oriented DBMS
Websiteaws.amazon.com/­cloudsearchspark.apache.org/­sqlwww.vertica.comwakanda.github.io
Technical documentationdocs.aws.amazon.com/­cloudsearchspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvertica.com/­documentationwakanda.github.io/­doc
DeveloperAmazonApache Software FoundationOpenText infopreviously Micro Focus and Hewlett PackardWakanda SAS
Initial release2012201420052012
Current release3.5.0 ( 2.13), September 202312.0.3, January 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial 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 languageScalaC++C++, JavaScript
Server operating systemshostedLinux
OS X
Windows
LinuxLinux
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 indexednoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like DML and DDL statementsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.no
APIs and other access methodsHTTP APIJDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
RESTful HTTP API
Supported programming languagesJava
Python
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
JavaScript
Server-side scripts infoStored proceduresnonoyes, PostgreSQL PL/pgSQL, with minor differencesyes
Triggersnonoyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredyes, utilizing Spark Corehorizontal partitioning, hierarchical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSnoneMulti-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 methodsnono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
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.nonono
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 CloudSearchSpark SQLVertica 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 CloudSearchSpark SQLVertica infoOpenText™ Vertica™WakandaDB
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