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DBMS > BigObject vs. Citus vs. etcd vs. eXtremeDB

System Properties Comparison BigObject vs. Citus vs. etcd vs. eXtremeDB

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonCitus  Xexclude from comparisonetcd  Xexclude from comparisoneXtremeDB  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA distributed reliable key-value storeNatively in-memory DBMS with options for persistency, high-availability and clustering
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSKey-value storeRelational DBMS
Time Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Websitebigobject.iowww.citusdata.cometcd.io
github.com/­etcd-io/­etcd
www.mcobject.com
Technical documentationdocs.bigobject.iodocs.citusdata.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.mcobject.com/­docs/­extremedb.htm
DeveloperBigObject, Inc.McObject
Initial release201520102001
Current release8.1, December 20183.4, August 20198.2, 2021
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2.0commercial
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 languageCGoC and C++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxFreeBSD
Linux
Windows infoexperimental
AIX
HP-UX
Linux
macOS
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.noyes infospecific XML type available, but no XML query functionalitynono infosupport of XML interfaces available
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard, with numerous extensionsnoyes infowith the option: eXtremeSQL
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC
JSON over HTTP
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C
C#
C++
Java
Lua
Python
Scala
Server-side scripts infoStored proceduresLuauser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes
Triggersnoyesyes, watching key changesyes infoby defining events
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning / sharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication infoother methods possible by using 3rd party extensionsUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Active Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes infoOptimistic (MVCC) and pessimistic (locking) strategies available
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.yesnonoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardno
More information provided by the system vendor
BigObjectCitusetcdeXtremeDB
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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BigObjectCitusetcdeXtremeDB
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