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DBMS > Google Cloud Bigtable vs. Google Cloud Spanner vs. Realm vs. Sphinx

System Properties Comparison Google Cloud Bigtable vs. Google Cloud Spanner vs. Realm vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonRealm  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.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value store
Wide column store
Relational DBMSDocument storeSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score2.69
Rank#101  Overall
#51  Relational DBMS
Score7.18
Rank#52  Overall
#8  Document stores
Score5.97
Rank#56  Overall
#5  Search engines
Websitecloud.google.com/­bigtablecloud.google.com/­spannerrealm.iosphinxsearch.com
Technical documentationcloud.google.com/­bigtable/­docscloud.google.com/­spanner/­docsrealm.io/­docssphinxsearch.com/­docs
DeveloperGoogleGoogleRealm, acquired by MongoDB in May 2019Sphinx Technologies Inc.
Initial release2015201720142001
Current release3.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemshostedhostedAndroid
Backend: server-less
iOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesno
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
Secondary indexesnoyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011noSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Proprietary protocol
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
.Net
Java infowith Android only
Objective-C
React Native
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonono inforuns within the applications so server-side scripts are unnecessaryno
Triggersnonoyes infoChange Listenersno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding 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 with 3 replicas for regional instances.nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownono
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 integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID infoStrict serializable isolationACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.nonoyes infoIn-Memory realm
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesno

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More resources
Google Cloud BigtableGoogle Cloud SpannerRealmSphinx
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