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DBMS > Hypertable vs. OpenMLDB vs. Vertica

System Properties Comparison Hypertable vs. OpenMLDB vs. Vertica

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonOpenMLDB  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.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopAn open-source machine learning database that provides a feature platform for training and inferenceCloud 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 modelWide column storeTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.02
Rank#367  Overall
#37  Time Series DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteopenmldb.aiwww.vertica.com
Technical documentationopenmldb.ai/­docs/­zh/­mainvertica.com/­documentation
DeveloperHypertable Inc.4 Paradigm Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release200920202005
Current release0.9.8.11, March 20162024-2 February 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen Sourcecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono 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 languageC++C++, Java, ScalaC++
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
LinuxLinux
Data schemeschema-freeFixed schemaYes, 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 datenoyesyes
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.nono
Secondary indexesrestricted infoonly exact value or prefix value scansyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsC++ API
Thrift
JDBC
SQLAlchemy
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++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelSource-replica replicationMulti-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 methodsyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
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.yesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
HypertableOpenMLDBVertica 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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HypertableOpenMLDBVertica infoOpenText™ Vertica™
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