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DBMS > EJDB vs. Google Cloud Bigtable vs. Solr vs. Tibero

System Properties Comparison EJDB vs. Google Cloud Bigtable vs. Solr vs. Tibero

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSolr  Xexclude from comparisonTibero  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A widely used distributed, scalable search engine based on Apache LuceneA secure RDBMS, designed for easy portability from Oracle
Primary database modelDocument storeKey-value store
Wide column store
Search engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#297  Overall
#44  Document stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score42.91
Rank#24  Overall
#3  Search engines
Score1.78
Rank#140  Overall
#64  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbcloud.google.com/­bigtablesolr.apache.orgus.tmaxsoft.com/­products/­tibero
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­bigtable/­docssolr.apache.org/­resources.htmltechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.html
DeveloperSoftmotionsGoogleApache Software FoundationTmaxSoft
Initial release2012201520062003
Current release9.6.0, April 20246, April 2015
License infoCommercial or Open SourceOpen Source infoGPLv2commercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaC and Assembler
Server operating systemsserver-lesshostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)AIX
HP-UX
Linux
Solaris
Windows
Data schemeschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idnoyes infosupports customizable data types and automatic typingyes
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.noyesyes
Secondary indexesnonoyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnonoSolr Parallel SQL Interfaceyes
APIs and other access methodsin-process shared librarygRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP/JSON API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresnonoJava pluginsPersistent Stored Procedure (PSM)
Triggersnonoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardinghorizontal partitioning infoby range, hash, list or composite
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possiblenonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyes
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.noyesno infoplanned for next version
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesfine grained access rights according to SQL-standard (SQL 92, SQL 99)

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More resources
EJDBGoogle Cloud BigtableSolrTibero
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