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DBMS > Google Cloud Bigtable vs. Infobright vs. Kinetica vs. Sphinx vs. Yaacomo

System Properties Comparison Google Cloud Bigtable vs. Infobright vs. Kinetica vs. Sphinx vs. Yaacomo

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonInfobright  Xexclude from comparisonKinetica  Xexclude from comparisonSphinx  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendFully vectorized database across both GPUs and CPUsOpen source search engine for searching in data from different sources, e.g. relational databasesOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelKey-value store
Wide column store
Relational DBMSRelational DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score1.02
Rank#192  Overall
#90  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitecloud.google.com/­bigtableignitetech.com/­softwarelibrary/­infobrightdbwww.kinetica.comsphinxsearch.comyaacomo.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.kinetica.comsphinxsearch.com/­docs
DeveloperGoogleIgnite Technologies Inc.; formerly InfoBright Inc.KineticaSphinx Technologies Inc.Q2WEB GmbH
Initial release20152005201220012009
Current release7.1, August 20213.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016commercialOpen Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC, C++C++
Server operating systemshostedLinux
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Android
Linux
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or datenoyesyesnoyes
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.nononono
Secondary indexesnono infoKnowledge Grid Technology used insteadyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsSQL-like query language (SphinxQL)yes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Proprietary protocolJDBC
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C++
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonouser defined functionsno
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononono
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 or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAMyes
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-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesAccess rights for users and roles on table levelnofine grained access rights according to SQL-standard

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More resources
Google Cloud BigtableInfobrightKineticaSphinxYaacomo
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