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DBMS > HugeGraph vs. Vertica vs. WakandaDB

System Properties Comparison HugeGraph vs. Vertica vs. WakandaDB

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Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSCloud 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 modelGraph 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
Score0.30
Rank#328  Overall
#29  Graph DBMS
Score14.36
Rank#42  Overall
#27  Relational DBMS
Score0.01
Rank#400  Overall
#22  Object oriented DBMS
Websitegithub.com/­hugegraph
hugegraph.apache.org
www.vertica.comwakanda.github.io
Technical documentationhugegraph.apache.org/­docsvertica.com/­documentationdoc.wakanda.org/­home2.en.html#/­Datastore/­Introduction.200-588937.en.html
DeveloperBaiduOpenText infopreviously Micro Focus and Hewlett PackardWakanda SAS
Initial release201820052012
Current release0.912.0.3, January 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial 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.
Vertica Accelerator’s high-performance analytics and machine learning with SQL or Python is available as SaaS.
Implementation languageJavaC++C++, JavaScript
Server operating systemsLinux
macOS
Unix
LinuxLinux
OS X
Windows
Data schemeyesYes, 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 indexesyes infoalso supports composite index and range indexNo 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 methodsJava API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
RESTful HTTP API
Supported programming languagesGroovy
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
JavaScript
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsyes, PostgreSQL PL/pgSQL, with minor differencesyes
Triggersnoyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBasehorizontal partitioning, hierarchical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseMulti-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 methodsvia hugegraph-sparkno infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphyes
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.yesnono
User concepts infoAccess controlUsers, roles and permissionsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashyes
More information provided by the system vendor
HugeGraphVertica 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,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
HugeGraphVertica infoOpenText™ Vertica™WakandaDB
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