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DBMS > Apache Phoenix vs. Google Cloud Bigtable vs. Ingres vs. RDF4J

System Properties Comparison Apache Phoenix vs. Google Cloud Bigtable vs. Ingres vs. RDF4J

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIngres  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Well established RDBMSRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitephoenix.apache.orgcloud.google.com/­bigtablewww.actian.com/­databases/­ingresrdf4j.org
Technical documentationphoenix.apache.orgcloud.google.com/­bigtable/­docsdocs.actian.com/­ingresrdf4j.org/­documentation
DeveloperApache Software FoundationGoogleActian CorporationSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release201420151974 infooriginally developed at University Berkely in early 1970s2004
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201911.2, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJava
Server operating systemsLinux
Unix
Windows
hostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
OS X
Unix
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonono infobut tools for importing/exporting data from/to XML-files available
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyesnoyesno
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsnoyesyes
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslynone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesIngres Replicatornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardno

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More resources
Apache PhoenixGoogle Cloud BigtableIngresRDF4J infoformerly known as Sesame
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