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DBMS > BigObject vs. eXtremeDB vs. Vertica

System Properties Comparison BigObject vs. eXtremeDB vs. Vertica

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisoneXtremeDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesNatively in-memory DBMS with options for persistency, high-availability and clusteringCloud 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 imposedRelational DBMS
Time Series DBMS
Relational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#333  Overall
#146  Relational DBMS
Score0.66
Rank#239  Overall
#109  Relational DBMS
#20  Time Series DBMS
Score11.76
Rank#44  Overall
#28  Relational DBMS
Websitebigobject.iowww.mcobject.comwww.vertica.com
Technical documentationdocs.bigobject.iowww.mcobject.com/­docs/­extremedb.htmvertica.com/­documentation
DeveloperBigObject, Inc.McObjectOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201520012005
Current release8.2, 202112.0.3, January 2023
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialcommercial 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and 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)
AIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
Data schemeyesyesYes, 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 dateyesyesyes
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 infosupport of XML interfaces availableno
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith the option: eXtremeSQLFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresLuayesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infoby defining eventsyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning / shardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Multi-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 methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyes
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.yesyesno
User concepts infoAccess controlnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
BigObjecteXtremeDBVertica infoOpenText™ Vertica™
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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Cost-based models and subscription-based models are both available. One license is...
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More resources
BigObjecteXtremeDBVertica infoOpenText™ Vertica™
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