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DBMS > Bangdb vs. Vertica vs. Yanza

System Properties Comparison Bangdb vs. Vertica vs. Yanza

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionConverged and high performance database for device data, events, time series, document and graphCloud 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.Time Series DBMS for IoT Applications
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMS infoColumn orientedTime Series DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitebangdb.comwww.vertica.comyanza.com
Technical documentationdocs.bangdb.comvertica.com/­documentation
DeveloperSachin Sinha, BangDBOpenText infopreviously Micro Focus and Hewlett PackardYanza
Initial release201220052015
Current releaseBangDB 2.0, October 202112.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoBSD 3commercial infoLimited community edition freecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++
Server operating systemsLinuxLinuxWindows
Data schemeschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.schema-free
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesno
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 infosecondary, composite, nested, reverse, geospatialNo Indexes Required. Different internal optimization strategy, but same functionality included.no
SQL infoSupport of SQLSQL like support with command line toolFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.no
APIs and other access methodsProprietary protocol
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
HTTP API
Supported programming languagesC
C#
C++
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
any language that supports HTTP calls
Server-side scripts infoStored proceduresnoyes, PostgreSQL PL/pgSQL, with minor differencesno
Triggersyes, Notifications (with Streaming only)yes, called Custom Alertsyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmhorizontal partitioning, hierarchical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Multi-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 systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modeno
User concepts infoAccess controlyes (enterprise version only)fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashno
More information provided by the system vendor
BangdbVertica infoOpenText™ Vertica™Yanza
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
BangdbVertica infoOpenText™ Vertica™Yanza
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