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DBMS > BigObject vs. eXtremeDB vs. Hawkular Metrics vs. Vitess

System Properties Comparison BigObject vs. eXtremeDB vs. Hawkular Metrics vs. Vitess

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisoneXtremeDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesNatively in-memory DBMS with options for persistency, high-availability and clusteringHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Scalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMS
Time Series DBMS
Time Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitebigobject.iowww.mcobject.comwww.hawkular.orgvitess.io
Technical documentationdocs.bigobject.iowww.mcobject.com/­docs/­extremedb.htmwww.hawkular.org/­hawkular-metrics/­docs/­user-guidevitess.io/­docs
DeveloperBigObject, Inc.McObjectCommunity supported by Red HatThe Linux Foundation, PlanetScale
Initial release2015200120142013
Current release8.2, 202115.0.2, December 2022
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++JavaGo
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
OS X
Windows
Docker
Linux
macOS
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith the option: eXtremeSQLnoyes infowith proprietary extensions
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
HTTP RESTADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
Go
Java
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresLuayesnoyes infoproprietary syntax
Triggersnoyes infoby defining eventsyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning / shardingSharding infobased on CassandraSharding
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
selectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes infotable locks or row locks depending on storage engine
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.yesyesnoyes
User concepts infoAccess controlnonoUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
BigObjecteXtremeDBHawkular MetricsVitess
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more

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BigObjecteXtremeDBHawkular MetricsVitess
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