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DBMS > Google Cloud Firestore vs. MarkLogic vs. Spark SQL vs. Teradata Aster vs. Trafodion

System Properties Comparison Google Cloud Firestore vs. MarkLogic vs. Spark SQL vs. Teradata Aster vs. Trafodion

Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTrafodion  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
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.Operational and transactional Enterprise NoSQL databaseSpark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and typesTransactional SQL-on-Hadoop DBMS
Primary database modelDocument storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.36
Rank#53  Overall
#9  Document stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitefirebase.google.com/­products/­firestorewww.marklogic.comspark.apache.org/­sqltrafodion.apache.org
Technical documentationfirebase.google.com/­docs/­firestoredocs.marklogic.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperGoogleMarkLogic Corp.Apache Software FoundationTeradataApache Software Foundation, originally developed by HP
Initial release20172001201420052014
Current release11.0, December 20223.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++, Java
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Windows
LinuxLinux
Data schemeschema-freeschema-free infoSchema can be enforcedyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.noyesnoyes infoin Aster File Storeno
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnoyes infoSQL92SQL-like DML and DDL statementsyesyes
APIs and other access methodsAndroid
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
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
Python
R
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsyes infovia XQuery or JavaScriptnoR packagesJava Stored Procedures
Triggersyes, with Cloud Functionsyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflowyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsyes infoSQL Map-Reduce Frameworkyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infocan act as a resource manager in an XA/JTA transactionnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, with Range Indexesnonono
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.Role-based access control at the document and subdocument levelsnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Google Cloud FirestoreMarkLogicSpark SQLTeradata AsterTrafodion
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