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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonIngres  Xexclude from comparisonKeyDB  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 RDBMSAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsRDF4J 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 DBMSKey-value storeRDF 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
Score0.71
Rank#226  Overall
#33  Key-value stores
Score0.69
Rank#230  Overall
#9  RDF stores
Websitecloud.google.com/­bigtablewww.actian.com/­databases/­ingresgithub.com/­Snapchat/­KeyDB
keydb.dev
rdf4j.org
Technical documentationcloud.google.com/­bigtable/­docsdocs.actian.com/­ingresdocs.keydb.devrdf4j.org/­documentation
DeveloperGoogleActian CorporationEQ Alpha Technology Ltd.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20151974 infooriginally developed at University Berkely in early 1970s20192004
Current release11.2, May 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD-3Open 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
LinuxLinux
OS X
Unix
Windows
Data schemeschema-freeyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or datenoyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
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 infoby using the Redis Search moduleyes
SQL infoSupport of SQLnoyesnono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Proprietary protocol infoRESP - REdis Serialization ProtocoJava 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
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Java
PHP
Python
Server-side scripts infoStored proceduresnoyesLuayes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslyShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesIngres ReplicatorMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDOptimistic locking, atomic execution of commands blocks and scriptsACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes 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
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-standardsimple password-based access control and ACLno

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More resources
Google Cloud BigtableIngresKeyDBRDF4J infoformerly known as Sesame
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