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DBMS > Apache Impala vs. Databricks vs. Kingbase vs. Microsoft Azure AI Search vs. MonetDB

System Properties Comparison Apache Impala vs. Databricks vs. Kingbase vs. Microsoft Azure AI Search vs. MonetDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonKingbase  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonMonetDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopThe 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.An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.Search-as-a-service for web and mobile app developmentA relational database management system that stores data in columns
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSSearch engineRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.45
Rank#262  Overall
#123  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score1.72
Rank#145  Overall
#67  Relational DBMS
Websiteimpala.apache.orgwww.databricks.comwww.kingbase.com.cnazure.microsoft.com/­en-us/­services/­searchwww.monetdb.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comlearn.microsoft.com/­en-us/­azure/­searchwww.monetdb.org/­Documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksBeiJing KINGBASE Information technologies inc.MicrosoftMonetDB BV
Initial release20132013199920152004
Current release4.1.0, June 2022V8.0, August 2021V1Dec2023 (11.49), December 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercialOpen Source infoMozilla Public License 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and JavaC
Server operating systemsLinuxhostedLinux
Windows
hostedFreeBSD
Linux
OS X
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyesyes
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.noyesyesno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLStandard with numerous extensionsnoyes infoSQL 2003 with some extensions
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
RESTful HTTP APIJDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C#
Java
JavaScript
Python
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesuser defined functionsnoyes, in SQL, C, R
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioningSharding infoImplicit feature of the cloud serviceSharding via remote tables
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyesyes infoImplicit feature of the cloud servicenone infoSource-replica replication available in experimental status
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID
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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardyes infousing Azure authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaDatabricksKingbaseMicrosoft Azure AI SearchMonetDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache ImpalaDatabricksKingbaseMicrosoft Azure AI SearchMonetDB
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