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DBMS > Google Cloud Bigtable vs. IBM Cloudant vs. Oracle Rdb vs. Rockset vs. Sphinx

System Properties Comparison Google Cloud Bigtable vs. IBM Cloudant vs. Oracle Rdb vs. Rockset vs. Sphinx

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonOracle Rdb  Xexclude from comparisonRockset  Xexclude from comparisonSphinx  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.Database as a Service offering based on Apache CouchDBA scalable, reliable search and analytics service in the cloud, built on RocksDBOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value store
Wide column store
Document storeRelational DBMSDocument storeSearch engine
Secondary database modelsRelational DBMS
Search engine
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
Score2.75
Rank#104  Overall
#19  Document stores
Score1.14
Rank#178  Overall
#80  Relational DBMS
Score0.82
Rank#212  Overall
#36  Document stores
Score5.95
Rank#55  Overall
#5  Search engines
Websitecloud.google.com/­bigtablewww.ibm.com/­products/­cloudantwww.oracle.com/­database/­technologies/­related/­rdb.htmlrockset.comsphinxsearch.com
Technical documentationcloud.google.com/­bigtable/­docscloud.ibm.com/­docs/­Cloudantwww.oracle.com/­database/­technologies/­related/­rdb-doc.htmldocs.rockset.comsphinxsearch.com/­docs
DeveloperGoogleIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014Oracle, originally developed by Digital Equipment Corporation (DEC)RocksetSphinx Technologies Inc.
Initial release20152010198420192001
Current release7.4.1.1, 20213.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangC++C++
Server operating systemshostedhostedHP Open VMShostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or datenonoyesdynamic typingno
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 infoingestion from XML files supported
Secondary indexesnoyesyesall fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLnonoyesRead-only SQL queries, including JOINsSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP/JSON APIHTTP RESTProprietary protocol
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
Java
JavaScript
Objective-C
PHP
Ruby
Go
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoView functions (Map-Reduce) in JavaScriptnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic shardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnonono
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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsno infoatomic operations within a document possibleyes, on a single nodenono
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databaseAccess rights for users and organizations can be defined via Rockset consoleno

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More resources
Google Cloud BigtableIBM CloudantOracle RdbRocksetSphinx
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