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DBMS > Databricks vs. Google Cloud Firestore vs. Kinetica vs. Postgres-XL

System Properties Comparison Databricks vs. Google Cloud Firestore vs. Kinetica vs. Postgres-XL

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonKinetica  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.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.Fully vectorized database across both GPUs and CPUsBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument store
Relational DBMS
Document storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websitewww.databricks.comfirebase.google.com/­products/­firestorewww.kinetica.comwww.postgres-xl.org
Technical documentationdocs.databricks.comfirebase.google.com/­docs/­firestoredocs.kinetica.comwww.postgres-xl.org/­documentation
DeveloperDatabricksGoogleKinetica
Initial release2013201720122014 infosince 2012, originally named StormDB
Current release7.1, August 202110 R1, October 2018
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C
Server operating systemshostedhostedLinuxLinux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesnonoyes infoXML type, but no XML query functionality
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLnoSQL-like DML and DDL statementsyes infodistributed, parallel query execution
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes, Firebase Rules & Cloud Functionsuser defined functionsuser defined functions
Triggersyes, with Cloud Functionsyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnoACID infoMVCC
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.noyes infoGPU vRAM or System RAMno
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 rights for users and roles on table levelfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksGoogle Cloud FirestoreKineticaPostgres-XL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGoogle Cloud FirestoreKineticaPostgres-XL
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