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DBMS > Google Cloud Bigtable vs. Ingres vs. Quasardb vs. RDF4J

System Properties Comparison Google Cloud Bigtable vs. Ingres vs. Quasardb vs. RDF4J

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonIngres  Xexclude from comparisonQuasardb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionGoogle'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 RDBMSDistributed, high-performance timeseries databaseRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelKey-value store
Wide column store
Relational DBMSTime Series DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitecloud.google.com/­bigtablewww.actian.com/­databases/­ingresquasar.airdf4j.org
Technical documentationcloud.google.com/­bigtable/­docsdocs.actian.com/­ingresdoc.quasar.ai/­masterrdf4j.org/­documentation
DeveloperGoogleActian CorporationquasardbSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20151974 infooriginally developed at University Berkely in early 1970s20092004
Current release11.2, May 20223.14.1, January 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++Java
Server operating systemshostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
BSD
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeschema-freeyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or datenoyesyes infointeger and binaryyes
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 infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesnoyesyes infowith tagsyes
SQL infoSupport of SQLnoyesSQL-like query languageno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
PHP
Python
Server-side scripts infoStored proceduresnoyesnoyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoconsistent hashingnone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesIngres ReplicatorSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes 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.nonoyes infoTransient mode
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardCryptographically strong user authentication and audit trailno

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More resources
Google Cloud BigtableIngresQuasardbRDF4J infoformerly known as Sesame
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