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DBMS > BigObject vs. eXtremeDB vs. Graph Engine vs. Solr

System Properties Comparison BigObject vs. eXtremeDB vs. Graph Engine vs. Solr

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisoneXtremeDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesNatively in-memory DBMS with options for persistency, high-availability and clusteringA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMS
Time Series DBMS
Graph DBMS
Key-value store
Search engine
Secondary database modelsSpatial 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
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score41.02
Rank#24  Overall
#3  Search engines
Websitebigobject.iowww.mcobject.comwww.graphengine.iosolr.apache.org
Technical documentationdocs.bigobject.iowww.mcobject.com/­docs/­extremedb.htmwww.graphengine.io/­docs/­manualsolr.apache.org/­resources.html
DeveloperBigObject, Inc.McObjectMicrosoftApache Software Foundation
Initial release2015200120102006
Current release8.2, 20219.6.1, May 2024
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialOpen Source infoMIT LicenseOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++.NET and CJava
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
.NETAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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 availablenoyes
Secondary indexesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith the option: eXtremeSQLnoSolr Parallel SQL Interface
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
RESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
C#
C++
F#
Visual Basic
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresLuayesyesJava plugins
Triggersnoyes infoby defining eventsnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning / shardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlnoyes
More information provided by the system vendor
BigObjecteXtremeDBGraph Engine infoformer name: TrinitySolr
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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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...
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BigObjecteXtremeDBGraph Engine infoformer name: TrinitySolr
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