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DBMS > BigObject vs. BoltDB vs. Kinetica vs. Vertica

System Properties Comparison BigObject vs. BoltDB vs. Kinetica vs. Vertica

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonBoltDB  Xexclude from comparisonKinetica  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesAn embedded key-value store for Go.Fully vectorized database across both GPUs and CPUsCloud 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 modelRelational DBMS infoa hierachical model (tree) can be imposedKey-value storeRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.74
Rank#220  Overall
#31  Key-value stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitebigobject.iogithub.com/­boltdb/­boltwww.kinetica.comwww.vertica.com
Technical documentationdocs.bigobject.iodocs.kinetica.comvertica.com/­documentation
DeveloperBigObject, Inc.KineticaOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015201320122005
Current release7.1, August 202112.0.3, January 2023
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoMIT Licensecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono 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 languageGoC, C++C++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
BSD
Linux
OS X
Solaris
Windows
LinuxLinux
Data schemeyesschema-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 dateyesnoyesyes
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 indexesyesnoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statementsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGoC++
Java
JavaScript (Node.js)
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresLuanouser defined functionsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneSource-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 methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnonenoneImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
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.yesnoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlnonoAccess rights for users and roles on table levelfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
BigObjectBoltDBKineticaVertica 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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More resources
BigObjectBoltDBKineticaVertica infoOpenText™ Vertica™
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