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DBMS > DataFS vs. Vertica vs. WakandaDB

System Properties Comparison DataFS vs. Vertica vs. WakandaDB

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Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Cloud 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 modelObject oriented DBMSRelational DBMS infoColumn orientedObject oriented DBMS
Secondary database modelsGraph DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#356  Overall
#17  Object oriented DBMS
Score12.46
Rank#45  Overall
#28  Relational DBMS
Score0.02
Rank#378  Overall
#18  Object oriented DBMS
Websitenewdatabase.comwww.vertica.comwakanda.github.io
Technical documentationdev.mobiland.com/­Overview.xspvertica.com/­documentationwakanda.github.io/­doc
DeveloperMobiland AGOpenText infopreviously Micro Focus and Hewlett PackardWakanda SAS
Initial release201820052012
Current release1.1.263, October 202212.0.3, January 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open Sourcecommercialcommercial infoLimited community edition freeOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++, JavaScript
Server operating systemsWindowsLinuxLinux
OS X
Windows
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)Yes, 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 dateyesyesyes
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 indexesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.no
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
RESTful HTTP API
Supported programming languages.Net
C
C#
C++
VB.Net
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
JavaScript
Server-side scripts infoStored proceduresyes, PostgreSQL PL/pgSQL, with minor differencesyes
Triggersno, except callback-events from server when changes happenedyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemhorizontal partitioning, hierarchical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlWindows-Profilefine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashyes
More information provided by the system vendor
DataFSVertica infoOpenText™ Vertica™WakandaDB
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
DataFSVertica infoOpenText™ Vertica™WakandaDB
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