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DBMS > Google Cloud Firestore vs. HBase vs. MarkLogic vs. Spark SQL

System Properties Comparison Google Cloud Firestore vs. HBase vs. MarkLogic vs. Spark SQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonHBase  Xexclude from comparisonMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionCloud 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.Wide-column store based on Apache Hadoop and on concepts of BigTableOperational and transactional Enterprise NoSQL databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeWide column storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.03
Rank#49  Overall
#8  Document stores
Score42.45
Rank#26  Overall
#2  Wide column stores
Score9.62
Rank#52  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#4  Search engines
Score23.72
Rank#35  Overall
#21  Relational DBMS
Websitefirebase.google.com/­products/­firestorehbase.apache.orgwww.marklogic.comspark.apache.org/­sql
Technical documentationfirebase.google.com/­docs/­firestorehbase.apache.orgdocs.marklogic.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetMarkLogic Corp.Apache Software Foundation
Initial release2017200820012014
Current release2.3.4, January 20219.0, 20173.3.0, June 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Scala
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-free, schema definition possibleschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes
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 indexesyesnoyesno
SQL infoSupport of SQLnonoyes infoSQL92SQL-like DML and DDL statements
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
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
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsyes infoCoprocessors in Javayes infovia XQuery or JavaScriptno
Triggersyes, with Cloud Functionsyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication
Source-replica replication
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflowyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesSingle row ACID (across millions of columns)ACID infocan act as a resource manager in an XA/JTA transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, with Range Indexesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACRole-based access control at the document and subdocument levelsno

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More resources
Google Cloud FirestoreHBaseMarkLogicSpark SQL
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