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DBMS > Google Cloud Bigtable vs. Google Cloud Firestore vs. MarkLogic vs. Memcached vs. Spark SQL

System Properties Comparison Google Cloud Bigtable vs. Google Cloud Firestore vs. MarkLogic vs. Memcached vs. Spark SQL

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMarkLogic  Xexclude from comparisonMemcached  Xexclude from comparisonSpark SQL  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.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Operational and transactional Enterprise NoSQL databaseIn-memory key-value store, originally intended for cachingSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value store
Wide column store
Document storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Key-value storeRelational DBMS
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
Score7.85
Rank#51  Overall
#8  Document stores
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score19.42
Rank#32  Overall
#4  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitecloud.google.com/­bigtablefirebase.google.com/­products/­firestorewww.marklogic.comwww.memcached.orgspark.apache.org/­sql
Technical documentationcloud.google.com/­bigtable/­docsfirebase.google.com/­docs/­firestoredocs.marklogic.comgithub.com/­memcached/­memcached/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleGoogleMarkLogic Corp.Danga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalApache Software Foundation
Initial release20152017200120032014
Current release11.0, December 20221.6.25, March 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial inforestricted free version is availableOpen Source infoBSD licenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CScala
Server operating systemshostedhostedLinux
OS X
Windows
FreeBSD
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-free infoSchema can be enforcedschema-freeyes
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.nonoyesno
Secondary indexesnoyesyesnono
SQL infoSupport of SQLnonoyes infoSQL92noSQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Proprietary protocolJDBC
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsyes infovia XQuery or JavaScriptnono
Triggersnoyes, with Cloud Functionsyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replicationyesnone infoRepcached, a Memcached patch, provides this functionallitynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesUsing Cloud Dataflowyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
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 integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsyesACID infocan act as a resource manager in an XA/JTA transactionnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, with Range Indexesno
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. Security Rules for 3rd party authentication using Firebase Auth.Role-based access control at the document and subdocument levelsyes infousing SASL (Simple Authentication and Security Layer) protocolno

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More resources
Google Cloud BigtableGoogle Cloud FirestoreMarkLogicMemcachedSpark SQL
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