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DBMS > Databricks vs. EDB Postgres vs. Google Cloud Firestore vs. Kinetica vs. Kingbase

System Properties Comparison Databricks vs. EDB Postgres vs. Google Cloud Firestore vs. Kinetica vs. Kingbase

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEDB Postgres  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonKinetica  Xexclude from comparisonKingbase  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.The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.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 CPUsAn enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.
Primary database modelDocument store
Relational DBMS
Relational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial 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
Score1.90
Rank#135  Overall
#63  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.45
Rank#262  Overall
#123  Relational DBMS
Websitewww.databricks.comwww.enterprisedb.comfirebase.google.com/­products/­firestorewww.kinetica.comwww.kingbase.com.cn
Technical documentationdocs.databricks.comwww.enterprisedb.com/­docsfirebase.google.com/­docs/­firestoredocs.kinetica.com
DeveloperDatabricksEnterpriseDBGoogleKineticaBeiJing KINGBASE Information technologies inc.
Initial release20132005201720121999
Current release14, December 20217.1, August 2021V8.0, August 2021
License infoCommercial or Open Sourcecommercialcommercial infoBSD for PostgreSQL-componentscommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC, C++C and Java
Server operating systemshostedLinux
Windows
hostedLinuxLinux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesyes infospecific XML-type available, but no XML query functionality.nonoyes
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyes infostandard with numerous extensionsnoSQL-like DML and DDL statementsStandard with numerous extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
Supported programming languagesPython
R
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes, Firebase Rules & Cloud Functionsuser defined functionsuser defined functions
Triggersyesyes, 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 nodeshorizontal partitioning infoby hash, list or rangeShardingShardinghorizontal partitioning (by range, list and hash) and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationMulti-source replicationSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
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.nonoyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess 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
DatabricksEDB PostgresGoogle Cloud FirestoreKineticaKingbase
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksEDB PostgresGoogle Cloud FirestoreKineticaKingbase
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