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DBMS > Hyprcubd vs. InfinityDB vs. Tkrzw vs. Vertica

System Properties Comparison Hyprcubd vs. InfinityDB vs. Tkrzw vs. Vertica

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Editorial information provided by DB-Engines
NameHyprcubd  Xexclude from comparisonInfinityDB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionServerless Time Series DBMSA Java embedded Key-Value Store which extends the Java Map interfaceA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetCloud 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.
Primary database modelTime Series DBMSKey-value storeKey-value storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#365  Overall
#55  Key-value stores
Score0.07
Rank#372  Overall
#57  Key-value stores
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitehyprcubd.com (offline)boilerbay.comdbmx.net/­tkrzwwww.vertica.com
Technical documentationboilerbay.com/­infinitydb/­manualvertica.com/­documentation
DeveloperHyprcubd, Inc.Boiler Bay Inc.Mikio HirabayashiOpenText infopreviously Micro Focus and Hewlett Packard
Initial release200220202005
Current release4.00.9.3, August 202012.0.3, January 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaC++C++
Server operating systemshostedAll OS with a Java VMLinux
macOS
Linux
Data schemeyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyes infotime, int, uint, float, stringyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysnoyes
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.nononono
Secondary indexesnono infomanual creation possible, using inversions based on multi-value capabilityNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languagenonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsgRPC (https)Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJavaC++
Java
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnononoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonenonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilitynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoOptimistic locking for transactions; no isolation for bulk loadsACID
Concurrency infoSupport for concurrent manipulation of datanoyesyesyes
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.nonoyes infousing specific database classesno
User concepts infoAccess controltoken accessnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
HyprcubdInfinityDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetVertica infoOpenText™ Vertica™
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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HyprcubdInfinityDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetVertica infoOpenText™ Vertica™
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