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DBMS > Heroic vs. Hypertable vs. Hyprcubd vs. Vertica

System Properties Comparison Heroic vs. Hypertable vs. Hyprcubd vs. Vertica

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonHypertable  Xexclude from comparisonHyprcubd  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchAn open source BigTable implementation based on distributed file systems such as HadoopServerless Time Series 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.
Primary database modelTime Series DBMSWide column storeTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitegithub.com/­spotify/­heroichyprcubd.com (offline)www.vertica.com
Technical documentationspotify.github.io/­heroicvertica.com/­documentation
DeveloperSpotifyHypertable Inc.Hyprcubd, Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release201420092005
Current release0.9.8.11, March 201612.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGNU version 3. Commercial license availablecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonoyesno infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++GoC++
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
hostedLinux
Data schemeschema-freeschema-freeyesYes, 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 dateyesnoyes infotime, int, uint, float, stringyes
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 infovia Elasticsearchrestricted infoonly exact value or prefix value scansnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnonoSQL-like query languageFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
C++ API
Thrift
gRPC (https)ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC++
Java
Perl
PHP
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 nodesShardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor on file system levelMulti-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 methodsnoyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesnoyes
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 controlnotoken accessfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
HeroicHypertableHyprcubdVertica 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,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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HeroicHypertableHyprcubdVertica infoOpenText™ Vertica™
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